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Article

The Prognostic Significance of Tumor-Infiltrating Lymphocytes, PD-L1, BRCA Mutation Status and Tumor Mutational Burden in Early-Stage High-Grade Serous Ovarian Carcinoma—A Study by the Spanish Group for Ovarian Cancer Research (GEICO)

by
David Pizarro
1,†,
Ignacio Romero
2,3,†,
Belén Pérez-Mies
1,4,5,
Andrés Redondo
3,6,7,8,
Tamara Caniego-Casas
1,4,
Irene Carretero-Barrio
1,4,5,
Eva Cristóbal
4,
Ana Gutiérrez-Pecharromán
9,
Ana Santaballa
3,10,
Emanuela D’Angelo
11,
David Hardisson
4,7,8,12,
Begoña Vieites
13,
Xavier Matías-Guiu
4,14,15,
Purificación Estévez
3,16,17,
Eva Guerra
3,18,
Jaime Prat
19,
Andrés Poveda
3,20,
José Antonio López-Guerrero
2,3,* and
José Palacios
1,3,4,5,*
1
Pathology Department, University Hospital Ramón y Cajal, IRYCIS, 28034 Madrid, Spain
2
Instituto Valenciano de Oncología, 46009 Valencia, Spain
3
Spanish Group for Investigation on Ovarian Cancer (GEICO), 28003 Madrid, Spain
4
Biomedical Research Network in Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
5
Faculty of Medicine, University of Alcalá, 28801 Alcalá de Henares, Spain
6
Oncology Department, University Hospital La Paz, IdiPAZ, 28046 Madrid, Spain
7
Instituto de Investigación Sanitaria del Hospital Universitario La Paz, 28029 Madrid, Spain
8
Faculty of Medicine, Autonomous University of Madrid, 28029 Madrid, Spain
9
Pathology Department, University Hospital Getafe, 28905 Getafe, Spain
10
Oncology Department, University Hospital La Fe, 46026 Valencia, Spain
11
Department of Medical, Oral, and Biotechnological Sciences, University “G.D’Annunzio” of Chieti-Pescara, 66013 Chieti, Italy
12
Pathology Department, University Hospital La Paz, 28046 Madrid, Spain
13
Pathology Department, University Hospital Virgen del Rocío, 41013 Sevilla, Spain
14
Pathology and Medical Oncology Departments, Hospital Universitari Arnau de Vilanova, IRBLLEIDA, University of Lleida, 25003 Lleida, Spain
15
Pathology Department, Hospital Universitari de Bellvitge, IDIBELL, University of Barcelona, 08007 Barcelona, Spain
16
Oncology Department, University Hospital Virgen del Rocío, 41013 Sevilla, Spain
17
Seville Biomedical Research Institute (IBIS), 41013 Sevilla, Spain
18
Oncology Department, University Hospital Ramón y Cajal, IRYCIS, 28034 Madrid, Spain
19
Pathology Department, Emeritus Faculty, Autonomous University of Barcelona, 08193 Barcelona, Spain
20
Initia Oncología, Hospital Quironsalud Valencia, 46010 Valencia, Spain
 
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*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2023, 24(13), 11183; https://doi.org/10.3390/ijms241311183
Submission received: 9 May 2023 / Revised: 25 June 2023 / Accepted: 28 June 2023 / Published: 6 July 2023
(This article belongs to the Special Issue Molecular Immunology of Solid Tumors, 2nd Edition)
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Abstract

:
Early stages are under-represented in studies on the molecular and immune features of high-grade serous ovarian carcinoma (HGSOC), and specific studies focused on early-stage HGSOC are required for a better prognostic stratification and to personalize chemotherapy. The aim of this study was to determine the prognostic significance of CD8+ and CD4+ tumor-infiltrating lymphocytes (TILs), tumoral cell PD-L1 expression, BRCA mutational status and tumor mutation burden (TMB) in early-stage HGSOC. A retrospective study was performed on stage I and II HGSOC from the Molecular Reclassification of Early Stages of Ovarian Cancer (RECLAMO) cohort from the Spanish Group of Ovarian Cancer Research (GEICO). Centralized histological typing was performed based on morphological and immunohistochemical features. Intraepithelial (i) and stromal (s) CD8+ and CD4+ T cells and PD-L1 were evaluated on tissue microarrays by immunohistochemistry. BRCA1 and BRCA2 mutation status and TMB were analyzed in tumor DNA using next-generation sequencing. The study included 124 tumors. High iCD8+ (>20 TILs/core), low/intermediate CD4+ (<20 TILs/core) and high CD8+/CD4+ ratio (>35/core) were associated with favorable outcomes. Tumor cell PD-L1 expression (TPS ≥ 1) was present in only 8% of tumors. In total, 11 (16%) and 6 (9%) out of 69 HGSOC tested carried pathogenic or likely pathogenic BRCA1 or BRCA2 mutations, respectively. Median TMB of 40 tumors analyzed was 5.04 mutations/Mb and only 6 tumors had 10 or more mutations/Mb. BRCA status and TMB were not associated with TILs or prognosis. When compared with studies on advanced HGSOC, our results suggested that prognostic variables differed according to stage and that more studies focused on early stages of HGSOC are needed to better stratify these tumors.

1. Introduction

There are five main histological types of ovarian carcinoma (OC): high-grade serous ovarian carcinoma (HGSOC), low-grade serous ovarian carcinoma (LGSOC), endometrioid ovarian carcinoma (EOC), clear cell ovarian carcinoma (CCOC) and mucinous ovarian carcinoma (MOC). These histological types differ in their precursor lesions, morphology, underlying molecular alterations, prognosis and response to treatment [1,2,3,4]. HGSOC is the most frequent and aggressive histological type of OC. Although most cases present in advanced stages, about 10–15% of patients debut in early stages (stage I and II) [5]. Due to their low frequency, there are few studies that analyze the molecular features and prognostic variables of early stage HGSOC [6].
Patients with HGSOC, even in early stages, are considered to have a high risk of relapse, so adjuvant chemotherapy is generally recommended. A better evaluation of this risk would allow chemotherapy to be personalized and reduce costs and treatment side effects in patients with low risk of relapse. For this reason, prognostic markers are needed to stratify patients and select those who will benefit from chemotherapy [7].
Some biomarkers related to the immune microenvironment or immune response have been analyzed as prognostic markers in OC. Nearly 20 years ago, Zhang et al. [8] reported for the first time an association between an increased number of intraepithelial (i) CD3+ cells and good prognosis in HGSOC. Since then, several studies have reported that prognosis was more directly related with the number of iCD8+ T cells [9,10]. However, most of these studies were focused on advanced HGSOC, and information regarding early stages has been very limited [11].
PD-L1 is currently used as a response predictor to immune checkpoint inhibitors (ICIs) in several types of cancers. Moreover, some studies have also tested its role as a possible prognostic marker in OC [12]. However, most studies were based on the analysis of advanced-stage tumors and have reported discordant results regarding not only the frequency of PD-L1 expression in tumor cells, but also whether or not PD-L1 is a marker of prognosis.
BRCA1 mutations have been related with increased immune cell infiltration in HGSOC [11,13]. In addition, advanced tumors with BRCA mutations seem to have a more favorable prognosis [14,15,16], probably due to the fact that they respond better to chemotherapy and PARP inhibitors (PARPi) due to homologous repair deficiency (HRD). The role of tumor mutational burden (TMB) as a prognostic or predictive marker has been scarcely studied in HGSOC [17,18,19,20] and its exact role as a possible biomarker in early-stage HGSOC remains to be established. Again, most studies reporting BRCA status and TMB as biomarkers were enriched in advanced-stage tumors.
A major limitation of most studies analyzing immune biomarkers in OC is that the histological type was assigned using only morphological criteria. Thus, after a centralized review using immunohistochemistry to complement morphological evaluation, it has been estimated that 20% of OC are assigned to a different histological type [2,21]. In this study, CD4+ and CD8+ TILs, PD-L1 expression, BRCA status and TMB were analyzed in a large series of early-stage HGSCs, in which histotyping had been performed using both morphological and immunohistochemical criteria, to analyze their impact on prognosis.

2. Results

2.1. Clinicopathological and Immunohistochemical Features

The series included 124 HGSOC, with a diagnosis based on both morphological and immunohistochemical criteria, as previously reported [2]. The diagnostic algorithm, which takes into account the expression of WT1, p53, Napsin A and PR was used to assist the classification of samples [21]. HGSOC were characterized by WT1+ and p53 abnormal pattern. In addition, most HGSC (87, 70.16%) showed diffuse nucleocytoplasmic expression of p16.
Due to the retrospective nature of the study and the multiple centers involved, some important clinical variables, such as family history, comorbidities, intraoperative findings or ascites cytology, were missing in our database. However, most patients were surgically staged and received a similar chemotherapy treatment. The main characteristics of this series are presented in Table 1 and Supplementary Table S1. HGSOC was diagnosed with a mean age of 57 years. Nearly half of the patients (59, 47.6%) were stage IC at diagnosis. Most patients (110, 92.4%) received platinum-based chemotherapy.
We evaluated the presence of CD4+ and CD8+ lymphocytes in the epithelium (iCD4+ and iCD8+) and stromal compartments (sCD4+ and sCD8+), counting the number of positive cells in each compartment. Each type of TIL was divided into the following three categories: no TILs, low/moderate TILs (1 to 19 lymphocytes) and high TILs (>20). The CD8+/CD4+ ratio was calculated in each compartment.
The most abundant lymphocyte population per core was iTILs-CD8+ (mean 49.55), followed by sTILs-CD8+ (mean 31.43), sTILs-CD4+ (mean 18) and iTILs-CD4+ (5.95) (Table 2 and Figure 1). The proportion of tumors with negative, low/moderate and high TILs is presented in Table 2. Whereas 60.8% of HGSOC in this series had high iCD8+TILs, only 10,7% of tumors had high iCD4+. The mean iCD8+/iCD4+ ratio was 35.75 and the median iCD8+/iCD4+ ratio was 15.50. No differences in any type of TILs or TIL ratios were observed according to stage (Supplementary Figure S1) or age.
Only 10 of 123 assessed tumors (8.1%) expressed PD-L1 in more than 1% of cells (TPS ≥ 1) and were considered positive. No association between PD-L1 expression and age or stage was observed. In contrast, PD-L1 expression was associated with TILs, and the number of all TIL categories was significantly higher in PD-L1-positive tumors (Figure 2).

2.2. BRCA1 and BRCA2 Mutational Status

DNA was extracted from all tumors, but only 72 rendered DNA of enough quality for molecular studies, and 69 of them gave valid results for BRCA analysis. In total, 11 (16%) and 6 (9%) out of 69 HGSOC carried pathogenic or likely pathogenic BRCA1 or BRCA2 mutations, respectively (Table 1 and Supplementary Table S2). No statistically significant associations were found between BRCA status and age or stage. Mutations in any or both BRCA genes were not associated with the number of TILs (Supplementary Figures S2–S4) or PD-L1.

2.3. Tumor Mutational Burden (TMB)

TMB analysis was performed in 62 tumors in which DNA was available after BRCA analysis. However, due to DNA quality, valid results were only obtained in 40 tumors (Table 1 and Supplementary Table S3). The median number of mutations/Mb was 5.04. Six tumors (15%) had 10 or more than 10 mutations/Mb. Two different thresholds were used to define high TMB, the median number of mutations/MB and >10 mutations/Mb. No association was found between TMB and any clinical variable, TILs (Supplementary Figure S5), PD-L1 or BRCA status (Supplementary Figure S6) using either of the two defined thresholds.

2.4. Survival Analysis

After a median follow-up of 85 months, 44 (35.5%) patients relapsed and 27 (21.7%) died (Figure 3). Age at diagnosis, iCD8+ (as a categorical variable), iCD4+ (as a categorical variable) and the ratio iCD8+/iCD4+ were associated with overall survival in the univariate analysis. Thus, patients younger than 56 years and tumors with high iTILs-CD8+ (>20), low/moderate iTILS-CD4+ (<20) and higher iCD8+/iCD4+ ratios (>35) had a longer survival (Figure 4 and Figure 5). In the multivariate analysis, only age, iCD8+ and iCD4+ remained as independent prognostic factors for overall survival (Figure 6). None of the other variables analyzed (stage, PD-L1, TMB, BRCA1 and BRCA2 mutations and BRCA status) were significantly associated with relapse-free survival or overall survival (Supplementary Figures S7–S10).

3. Discussion

In this series of early-stage HGSOC, centralized histotyping was performed using both histological and immunohistochemical features. We observed a prognosis similar to that reported in the literature for early-stage HGSOC, with an overall survival at 120 months of around 70% [22,23]. Some studies report slightly worse outcomes, with around 50% survival at 120 months [24].
We observed that high iCD8+ infiltration was associated to a favorable prognosis. Our results confirmed the observation of the only previously reported study with a large number of early-stage HGSOC, as well as the results of most previous series in advanced-stage HGSOC [9,10,11]. From a clinical and diagnostic point of view, the best TIL cut-off to stratify prognosis remains to be established, since some studies, such as the one presented here, have used TMA, whereas others have used whole tissue sections. In addition, the cut-off was variable among studies. To take into account intratumoral heterogeneity in TILs across cores per patient, the average value of the two core counts was used, as reported by other authors [25]. In contrast, Goode et al. [11] used the maximum TIL count per high-power microscopic field. At present, whether evaluating hot-spot areas of TILs provides better prognostic information than the average count has not been established. In other tumors, such as breast cancer, where TILs have been associated with prognosis and therapy response, it is recommended to evaluate average TILs. As previously suggested by Goode et al. [11], a practical and robust scoring system should be developed for TILs in HGSOC.
In addition to increased iCD8+, we observed that the prognosis was more favorable in tumors with low/moderate iCD4+ infiltration. The role of iCD4+ in early-stage HGSOC has not yet been established. The study of Goode et al. [11] did not include CD4 analysis and other studies mainly focused on advanced stages. Whereas Hao et al. [9] reported in their meta-analysis that increased iCD4 was associated with favorable prognosis, this association was not observed in the meta-analysis by Li et al. [10]. The unfavorable effect of CD4+ cells on prognosis in advanced HGSOC reported in some series has been related with an increase in FOXP3+ cells, although not all studies have confirmed this association [10]. Preston et al. [26] and Sato et al. [27] suggested that the effector/suppressor ratio CD8+/CD4+ may be a more important indicator of outcome than individual cell count. Accordingly, we found that high CD8+/CD4+ ratio was associated with a favorable prognosis in the univariate analysis, but this association was lost in the multivariate analysis.
We observed that only 8% of early-stage HGSOC in this series expressed PD-L1 in tumor cells and that this expression was not associated with prognosis. Series that analyzed PD-L1 in HGSOC are heterogeneous in terms of clinicopathological features, staining assays, cut-off values and the evaluation of tumor cells, inflammatory cells or both [28,29,30,31,32,33,34]. In previous studies, the percentage of positive tumor cells ranged from 24% [28] to 88% [29]. The low percentage of tumor cell positivity in our series is probably related to the analysis of only early-stage tumors. Thus, Wang et al. [28] reported that 24% of HGSC (n = 107) in their series expressed PD-L1 in tumor cells, but this percentage dropped to 7.7% in early-stage tumors (n = 26). In addition, a recent meta-analysis by Zhang and Yang reported that PD-L1 tumor cell positivity was correlated to advanced FIGO stages [30].
The prognostic significance of PD-L1 in ovarian cancer is controversial, with studies indicating its association with both a favorable and unfavorable prognosis. Some series [12] and the meta-analysis by Zhang and Yang [30] that included all stages suggested that PD-L1 expression on inflammatory cells was associated with a favorable prognosis. These authors [30] also reported a better response to ICIs, although the number of studies was limited. Moreover, findings from recent clinical trials suggest that PD-L1 could help selecting patients for ICIs, although the PD-L1 cut-off to be used is not yet defined [35,36].
BRCA1 and BRCA2 mutations were present in 24.6% (17/69) of tumors in this series, a similar frequency to that reported in The Cancer Genome Atlas Program (TCGA) [15]. We did not observe association between BRCA1 nor BRCA2 status with TILs. In contrast, some studies have reported that tumors with BRCA1 germline mutations had increased iTILs. Thus, Goode et al. [11] reported in their series of mainly advanced-stage HGSOC that the extent of CD8+ TILs differed significantly by mutation status, as 29% of BRCA1 mutation carriers had high TIL counts (≥20 iCD8+/HPF), compared to only 18% of non-carriers and 15% BRCA2 mutation carriers. Similarly, Morse et al. [37] found higher counts of CD3+ TILs in tumors with BRCA1 mutations or with mutations in HRD genes. The series included all histological types and stages but was enriched in advanced-stage HGSOC. Soslow et al. [13] reported an increased number of iTILs (without immunophenotyping) in tumors with BRCA1 alterations (mutations and promoter hypermethylation; n = 23) than in BRCA2+ (n = 8) and BRCA- tumors (n = 13). Although this study did not report the stage of the tumors, they were selected from the TCGA series that mainly included advanced stages. The intrinsic heterogeneity of HGSOC may justify our findings. In fact, immune response is an evolutionary process that depends on multiple factors, such as the anatomical site, tumor progression and mutational status [38].
Although some series [39] and meta-analysis [16,40] have reported an association of BRCA1/2 mutation and good prognosis, we did not observe this association. However, as previously stated, most studies included advanced-stage HGSOC. In the meta-analysis reported by Bolton et al. [14], the authors observed a better prognosis at 5 years of BRCA1/2 mutated tumors, but the association was lost when the analysis was restricted to stage I and II OC, even though the series included all histological types. In addition, it has been suggested that the survival advantage associated with BRCA status decreases over time [40,41].
In this series, we observed low TMB among early-stage HGSC. Thus, only 15% of tumors had >10 mut/Mb, but three of them had less than 11 mut/Mb. Several studies have analyzed TMB mostly in advanced HGSC, using different methodologies, but no study has focused exclusively on early stages. Some authors have re-evaluated data from the TCGA and have observed a median TMB of around 2 mut/Mb. Zhong et al. [18] reported 5.2 mutations/Mb (range 0–39 mutations/Mb) in 88 HGSC (15% in early stage), but only four (4.5%) had more than 10 mutations/Mb. The authors did not study the differences among stages. Liu et al. [17] analyzed 45 recurrent advanced HGSC and observed a median TMB of 3.4 mut/Mb. The authors did not observe any case with TMB > 10 mut/Mb. Zhang et al. [20] studied 65 ovarian cancer patients (50 HGSC, 20% stage I and II) and found a median TMB of 4.1 mut/Mb (0.6–23.2). The authors did not analyze differences among histological types or stages.
In our series, TMB was not associated with prognosis after using two cut-offs, the median TMB and >10 mut/Mb. Studies analyzing TCGA data have observed that tumors with a higher TMB, as defined by the median value of about 2 mut/Mb, had a better prognosis [42]. Yang et al. [19] reported that stage III HGSOC from 20 long-term survivors had an increased somatic mutation burden when compared with 21 short-term survivors, but TMB was low in both groups (median 1.62 vs. 1.22 nonsynonymous mutations/Mb).
Regarding therapy response, Liu et al. [17] did not observe an association between TMB and survival or response to ICIs in their series of recurrent heavily treated tumors. Cristescu et al. [43] re-analyzed TMB by WES in 12 clinical trials of advanced HGSOC and, using a cut-off of 175 mut/exome, observed high TMB in 12/293 (4.1%) tumors (histological type not specified). Responses to pembrolizumab were observed in 2 of 12 (16.7%) tumors with high TMB and in 21 out of 281 (7.5%) tumors with low TMB.
TMB in our series did not differ between HGSOC with and without BRCA mutations. In contrast, Liu et al. [17] reported that TMB was significantly higher in BRCA1/2 mutated advanced HGSC (n = 11, mean around 6 mut/MB) than in wild-type tumors (n = 53, mean around 3 mut/MB), but the analysis included all histologies.
One limitation of this study was the use of TMA for semiquantitative TIL estimation. Future studies using whole slide images and digital quantitation would help in stablishing a practical robust threshold for prognostication. An additional limitation was that not all tumors in this series were molecularly characterized due to poor DNA quality associated with old samples.
On the other hand, major strengths in this study included a relatively large series of tumors in an early stage and centralized histotyping using both morphological and immunohistochemical features.
The assignation of the histological type is not difficult in most ovarian carcinomas. However, there are tumors with an ambiguous morphology, mainly high-grade tumors, where histotyping errors have been reported in up to 30% of cases [44]. For this reason, the use of immunohistochemistry is recommended to refine histological typing. Thus, the use of a short immunohistochemical panel including WT1, p53, Napsin A and progesterone receptor, together with the morphological evaluation, provides an excellent agreement among pathologists [21].

4. Materials and Methods

4.1. Pathology and Immunohistochemistry

This series of HGSC comes from the RECLAMO study (acronym derived from the project titled Molecular Reclassification of Early Stages of Ovarian Cancer: predictive and prognostic impact) from the Spanish Group of Ovarian Cancer Research (GEICO). Cases had paraffin-embedded tumor samples available and >5 years of clinical follow-up. Approval for the RECLAMO study was obtained from the Local Ethics Committees and written informed consent was obtained from all study participants [2].
Immunohistochemistry (IHC) of tissue microarrays (TMAs) was performed as previously reported [2,45,46]. TMA cores of 1 mm diameter were evaluated for the presence of CD4+ (clone 4B12, Agilent, Santa Clara, CA, USA) and CD8+ (clone C8/114B, Agilent, Santa Clara, CA, USA) lymphocytes. Since two cores were evaluated in most tumors, the average count per core was used for statistical analysis.
PD-L1 IHC testing was performed using the DAKO 22C3 PharmDx (Agilent, Santa Clara, USA) assay according to the manufacturer’s instructions. PD-L1 IHC slides were interpreted using the tumor proportion score (TPS), which is the number of PD-L1 stained tumor cells divided by the total number of viable tumor cells, multiplied by 100. A TPS ≥ 1 was considered positive for PD-L1.

4.2. BRCA1 and BRCA2 Mutation Analysis

BRCA1 and BRCA2 gene status was evaluated using the Oncomine BRCA Research Assay Panel (Ion Torrent, Thermo Fisher Scientific, Waltham, MA, USA). This assay is based on highly multiplexed amplification that allows the detection of BRCA1 and BRCA2 gene variants in somatic and germline samples. The Ion Chef Instrument (Ion Torrent, Thermo Fisher Scientific, MA, USA) was used for the automated library preparation. Next-generation sequencing (NGS) libraries were sequenced with the Ion S5 using the Ion 530 Chef Kit (Thermo Fisher Scientific, Waltham, MA, USA). DNA sequencing data were accessed through the Torrent Suite program (5.12 version—Thermo Fisher Scientific, Waltham, MA, USA). Reads were aligned with the GRCh37-hg19 human reference genome, and potential mutations and copy number alteration were called using the Ion Reporter™ Cloud Software (5.16 version—Thermo Fisher Scientific, Waltham, MA, USA). These processes were performed following the manufacturers’ instructions. In addition, a filter analysis was incorporated selecting only those variants with >500 reads and an allelic frequency >5%. The variant calls were manually checked using the integrative genomics viewer (IGV; Broad Institute, Cambridge, MA, USA); germline and somatic pathogenic or probably pathogenic mutations were not differentiated since normal tissue was not available for most tumors.

4.3. TMB

For DNA extraction, paraffin blocks were punched within the tumor area selected in hematoxylin and eosin stained tissue sections to ensure a minimum of 30% of tumor cells. DNA was extracted using QIAamp DNA FFPE Tissue Kit (Qiagen, Valencia, CA, USA) following the manufacturer’s instructions. The Qubit dsDNA Broad-Range assay kit (Invitrogen, Waltham, MA, USA) was used to quantify DNA and qualitative assessment was performed with the Tape Station 2200 and Genomic DNA Kit (Agilent, Santa Clara, CA, USA).
The Oncomine Tumor Mutation Load Assay Panel (Ion Torrent, Thermo Fisher Scientific, Waltham, MA, USA) was used to assess TMB as previously reported (22). The assay covers 1.65 Mb across 409 relevant oncogenes across major cancer types. The Ion Chef Instrument (Ion Torrent, Thermo Fisher Scientific, Waltham, MA, USA) was used for automated library preparations. NGS libraries were sequenced in an Ion S5 using the Ion 540 Chef Kit (Thermo Fisher Scientific, Waltham, MA, USA). DNA sequencing data were accessed through the Torrent Suite program (5.12 version—Thermo Fisher Scientific, Waltham, MA, USA). Reads were aligned with the GRCh37-hg19 human reference genome, and alterations were called using the Ion Reporter™ Cloud Software (5.16 version—Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions. This platform uses germline filtering with 1000 genomes, 5000 exomes and ExAC databases; nonsynonymous variants are accurately called and assessed for TMB (mutations/Mb). In addition, an analysis filter that increased the value of the minimum allele frequency from 0.05 to 0.1 was incorporated because the high degradation of old paraffin samples produces a large number of low-frequency variants that can distort the results.

4.4. Statistical Analysis

Differences in continuous variables were assessed using the Wilcoxon rank-sum test and differences between categorical variables were assessed using the Fisher test for contingency tables.
Relapse-free survival was calculated as the time interval between the diagnosis of HGSOC and first confirmed sign of disease relapse. Overall survival was defined as the time interval between the diagnosis of HGSOC and the date of death or end of follow-up. For survival analysis, the Kaplan–Meier method was used to estimate relapse-free survival and overall survival curves. Only p values < 0.05 were considered significant. Finally, multivariate Cox proportional hazard models were carried out to assess hazard ratios associated with each significant risk factor.

5. Conclusions

In summary, our results suggested a prognostic role of iTILs in early-stage HGSOC. The role of PD-L1, BRCA status and TMB remains to be established, since most studies were not focused on these stages, included patients with different clinico-pathological characteristics and used different methodologies and cut-offs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms241311183/s1.

Author Contributions

J.A.L.-G. and J.P. (José Palacios) performed study concept and design; I.R., B.P.-M., A.R., I.C.-B., A.S., E.D., D.H., E.G., J.P. (Jaime Prat), A.P. and J.P. (José Palacios) performed development of methodology and writing, review and revision of the paper; D.P., I.C.-B., A.G.-P., B.V., X.M.-G., P.E. and J.P. (José Palacios) provided acquisition, analysis and interpretation of data and statistical analysis; T.C.-C. and E.C. provided technical and material support. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Instituto de Salud Carlos III (ISCIII) (grants PI19/01331, PI22/01892 and PMP22/00054); CIBERONC (grant CB16/12/00316); European Development Regional Fund ‘A way to achieve Europe’ (FEDER), Spanish Group of Research in Ovarian Cancer (GEICO group); and by the Spanish Association Against Cancer Scientific Foundation (AECC).

Institutional Review Board Statement

The study was approved by the Fundación Instituto Valenciano de Oncología Clinical Investigation Research Ethics Committee (Tittle: “Reclasifición molecular de estadios iniciales de cáncer de ovario, implicaciones pronósticas y predictivas”, GEICO 1201T trial). The study was performed in accordance with the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors thank the support of the GEICO’s Technical Secretary for co-ordinating the collection of tumor samples from all the hospitals involved. They also thank all the pathologists, clinicians and patients involved in the Early Stage Registry of Ovarian Cancer.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Romero, I.; Leskelä, S.; Mies, B.P.; Velasco, A.P.; Palacios, J. Morphological and Molecular Heterogeneity of Epithelial Ovarian Cancer: Therapeutic Implications. Eur. J. Cancer Suppl. 2020, 15, 1–15. [Google Scholar] [CrossRef] [PubMed]
  2. Leskela, S.; Romero, I.; Cristobal, E.; Pérez-Mies, B.; Rosa-Rosa, J.M.; Gutierrez-Pecharroman, A.; Santón, A.; Gonzalez, B.O.; López-Reig, R.; Hardisson, D.; et al. The Frequency and Prognostic Significance of the Histologic Type in Early-Stage Ovarian Carcinoma: A Reclassification Study by the Spanish Group for Ovarian Cancer Research (GEICO). Am. J. Surg. Pathol. 2020, 44, 149–161. [Google Scholar] [CrossRef] [PubMed]
  3. Prat, J. Ovarian Carcinomas: Five Distinct Diseases with Different Origins, Genetic Alterations, and Clinicopathological Features. Virchows Arch. 2012, 460, 237–249. [Google Scholar] [CrossRef]
  4. Prat, J.; D’Angelo, E.; Espinosa, I. Ovarian Carcinomas: At Least Five Different Diseases with Distinct Histological Features and Molecular Genetics. Hum. Pathol. 2018, 80, 11–27. [Google Scholar] [CrossRef] [PubMed]
  5. Collinson, F.; Qian, W.; Fossati, R.; Lissoni, A.; Williams, C.; Parmar, M.; Ledermann, J.; Colombo, N.; Swart, A. Optimal Treatment of Early-Stage Ovarian Cancer. Ann. Oncol. 2014, 25, 1165–1171. [Google Scholar] [CrossRef] [PubMed]
  6. Cheng, Z.; Mirza, H.; Ennis, D.P.; Smith, P.; Morrill Gavarró, L.; Sokota, C.; Giannone, G.; Goranova, T.; Bradley, T.; Piskorz, A.; et al. The Genomic Landscape of Early-Stage Ovarian High-Grade Serous Carcinoma. Clin. Cancer Res. 2022, 28, 2911–2922. [Google Scholar] [CrossRef] [PubMed]
  7. Kulbe, H.; Klein, O.; Wu, Z.; Taube, E.T.; Kassuhn, W.; Horst, D.; Darb-Esfahani, S.; Jank, P.; Abobaker, S.; Ringel, F.; et al. Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging. Cancers 2020, 12, 2000. [Google Scholar] [CrossRef]
  8. Zhang, L.; Conejo-Garcia, J.R.; Katsaros, D.; Gimotty, P.A.; Massobrio, M.; Regnani, G.; Makrigiannakis, A.; Gray, H.; Schlienger, K.; Liebman, M.N.; et al. Intratumoral T Cells, Recurrence, and Survival in Epithelial Ovarian Cancer. N. Engl. J. Med. 2003, 348, 203–213. [Google Scholar] [CrossRef] [Green Version]
  9. Hao, J.; Yu, H.; Zhang, T.; An, R.; Xue, Y. Prognostic Impact of Tumor-Infiltrating Lymphocytes in High Grade Serous Ovarian Cancer: A Systematic Review and Meta-Analysis. Ther. Adv. Med. Oncol. 2020, 12, 175883592096724. [Google Scholar] [CrossRef]
  10. Li, J.; Wang, J.; Chen, R.; Bai, Y.; Lu, X. The Prognostic Value of Tumor-Infiltrating T Lymphocytes in Ovarian Cancer. Oncotarget 2017, 8, 15621–15631. [Google Scholar] [CrossRef] [Green Version]
  11. Ovarian Tumor Tissue Analysis (OTTA) Consortium. Dose-Response Association of CD8+ Tumor-Infiltrating Lymphocytes and Survival Time in High-Grade Serous Ovarian Cancer. JAMA Oncol. 2017, 3, e173290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Webb, J.R.; Milne, K.; Kroeger, D.R.; Nelson, B.H. PD-L1 Expression Is Associated with Tumor-Infiltrating T Cells and Favorable Prognosis in High-Grade Serous Ovarian Cancer. Gynecol. Oncol. 2016, 141, 293–302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Soslow, R.A.; Han, G.; Park, K.J.; Garg, K.; Olvera, N.; Spriggs, D.R.; Kauff, N.D.; Levine, D.A. Morphologic Patterns Associated with BRCA1 and BRCA2 Genotype in Ovarian Carcinoma. Mod. Pathol. 2012, 25, 625–636. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Bolton, K.L.; Chenevix-Trench, G.; Goh, C.; Sadetzki, S.; Ramus, S.J.; Karlan, B.Y.; Lambrechts, D.; Despierre, E.; Barrowdale, D.; McGuffog, L.; et al. Association between BRCA1 and BRCA2 Mutations and Survival in Women with Invasive Epithelial Ovarian Cancer. JAMA 2012, 307, 382–390. [Google Scholar] [CrossRef] [Green Version]
  15. The Cancer Genome Atlas Program—NCI. Available online: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga (accessed on 11 August 2022).
  16. Nahshon, C.; Barnett-Griness, O.; Segev, Y.; Schmidt, M.; Ostrovsky, L.; Lavie, O. Five-Year Survival Decreases over Time in Patients with BRCA-Mutated Ovarian Cancer: A Systemic Review and Meta-Analysis. Int. J. Gynecol. Cancer 2022, 32, 48–54. [Google Scholar] [CrossRef]
  17. Liu, Y.L.; Selenica, P.; Zhou, Q.; Iasonos, A.; Callahan, M.; Feit, N.Z.; Boland, J.; Vazquez-Garcia, I.; Mandelker, D.; Zehir, A.; et al. BRCA Mutations, Homologous DNA Repair Deficiency, Tumor Mutational Burden, and Response to Immune Checkpoint Inhibition in Recurrent Ovarian Cancer. JCO Precis. Oncol. 2020, 4, 665–679. [Google Scholar] [CrossRef]
  18. Zhong, F.; Zhu, T.; Pan, X.; Zhang, Y.; Yang, H.; Wang, X.; Hu, J.; Han, H.; Mei, L.; Chen, D.; et al. Comprehensive Genomic Profiling of High-grade Serous Ovarian Carcinoma from Chinese Patients Identifies Co-occurring Mutations in the Ras/Raf Pathway with TP53. Cancer Med. 2019, 8, 3928–3935. [Google Scholar] [CrossRef] [Green Version]
  19. Yang, S.Y.C.; Lheureux, S.; Karakasis, K.; Burnier, J.V.; Bruce, J.P.; Clouthier, D.L.; Danesh, A.; Quevedo, R.; Dowar, M.; Hanna, Y.; et al. Landscape of Genomic Alterations in High-Grade Serous Ovarian Cancer from Exceptional Long- and Short-Term Survivors. Genome Med. 2018, 10, 81. [Google Scholar] [CrossRef] [Green Version]
  20. Zhang, Y.; Shi, X.; Zhang, J.; Chen, X.; Zhang, P.; Liu, A.; Zhu, T. A Comprehensive Analysis of Somatic Alterations in Chinese Ovarian Cancer Patients. Sci. Rep. 2021, 11, 387. [Google Scholar] [CrossRef]
  21. Köbel, M.; Rahimi, K.; Rambau, P.F.; Naugler, C.; Le Page, C.; Meunier, L.; de Ladurantaye, M.; Lee, S.; Leung, S.; Goode, E.L.; et al. An Immunohistochemical Algorithm for Ovarian Carcinoma Typing. Int. J. Gynecol. Pathol. 2016, 35, 430–441. [Google Scholar] [CrossRef] [Green Version]
  22. Nasioudis, D.; Mastroyannis, S.A.; Ko, E.M.; Haggerty, A.F.; Cory, L.; Giuntoli, R.L.; Kim, S.H.; Morgan, M.A.; Latif, N.A. Delay in Adjuvant Chemotherapy Administration for Patients with FIGO Stage I Epithelial Ovarian Carcinoma Is Associated with Worse Survival; an Analysis of the National Cancer Database. Gynecol. Oncol. 2022, 166, 263–268. [Google Scholar] [CrossRef] [PubMed]
  23. van Baal, J.O.A.M.; Van de Vijver, K.K.; Algera, M.D.; van der Aa, M.A.; Sonke, G.S.; van Driel, W.J.; Kenter, G.G.; Amant, F.C.; Lok, C.A.R. The Effect of Adjuvant Chemotherapy on Survival in Patients with FIGO Stage I High-Grade Serous Ovarian Cancer. Gynecol. Oncol. 2019, 153, 562–567. [Google Scholar] [CrossRef]
  24. Le Page, C.; Rahimi, K.; Köbel, M.; Tonin, P.N.; Meunier, L.; Portelance, L.; Bernard, M.; Nelson, B.H.; Bernardini, M.Q.; Bartlett, J.M.S.; et al. Characteristics and Outcome of the COEUR Canadian Validation Cohort for Ovarian Cancer Biomarkers. BMC Cancer 2018, 18, 347. [Google Scholar] [CrossRef]
  25. Webb, J.R.; Milne, K.; Watson, P.; deLeeuw, R.J.; Nelson, B.H. Tumor-Infiltrating Lymphocytes Expressing the Tissue Resident Memory Marker CD103 Are Associated with Increased Survival in High-Grade Serous Ovarian Cancer. Clin. Cancer Res. 2014, 20, 434–444. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Preston, C.C.; Maurer, M.J.; Oberg, A.L.; Visscher, D.W.; Kalli, K.R.; Hartmann, L.C.; Goode, E.L.; Knutson, K.L. The Ratios of CD8+ T Cells to CD4+CD25+ FOXP3+ and FOXP3- T Cells Correlate with Poor Clinical Outcome in Human Serous Ovarian Cancer. PLoS ONE 2013, 8, e80063. [Google Scholar] [CrossRef] [Green Version]
  27. Sato, E.; Olson, S.H.; Ahn, J.; Bundy, B.; Nishikawa, H.; Qian, F.; Jungbluth, A.A.; Frosina, D.; Gnjatic, S.; Ambrosone, C.; et al. Intraepithelial CD8+ Tumor-Infiltrating Lymphocytes and a High CD8+ Regulatory T Cell Ratio Are Associated with Favorable Prognosis in Ovarian Cancer. Proc. Natl. Acad. Sci. USA 2005, 102, 18538–18543. [Google Scholar] [CrossRef]
  28. Wang, Q.; Lou, W.; Di, W.; Wu, X. Prognostic Value of Tumor PD-L1 Expression Combined with CD8 + Tumor Infiltrating Lymphocytes in High Grade Serous Ovarian Cancer. Int. Immunopharmacol. 2017, 52, 7–14. [Google Scholar] [CrossRef]
  29. Darb-Esfahani, S.; Kunze, C.A.; Kulbe, H.; Sehouli, J.; Wienert, S.; Lindner, J.; Budczies, J.; Bockmayr, M.; Dietel, M.; Denkert, C.; et al. Prognostic Impact of Programmed Cell Death-1 (PD-1) and PD-Ligand 1 (PD-L1) Expression in Cancer Cells and Tumor-Infiltrating Lymphocytes in Ovarian High Grade Serous Carcinoma. Oncotarget 2016, 7, 1486–1499. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Zhang, C.; Yang, Q. Predictive Values of Programmed Cell Death-Ligand 1 Expression for Prognosis, Clinicopathological Factors, and Response to Programmed Cell Death-1/Programmed Cell Death-Ligand 1 Inhibitors in Patients with Gynecological Cancers: A Meta-Analysis. Front. Oncol. 2021, 10, 572203. [Google Scholar] [CrossRef]
  31. Whitehair, R.; Peres, L.C.; Mills, A.M. Expression of the Immune Checkpoints LAG-3 and PD-L1 in High-Grade Serous Ovarian Carcinoma: Relationship to Tumor-Associated Lymphocytes and Germline BRCA Status. Int. J. Gynecol. Pathol. 2020, 39, 558–566. [Google Scholar] [CrossRef]
  32. Martin de la Fuente, L.; Westbom-Fremer, S.; Arildsen, N.S.; Hartman, L.; Malander, S.; Kannisto, P.; Måsbäck, A.; Hedenfalk, I. PD-1/PD-L1 Expression and Tumor-Infiltrating Lymphocytes Are Prognostically Favorable in Advanced High-Grade Serous Ovarian Carcinoma. Virchows Arch. 2020, 477, 83–91. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Chen, H.; Molberg, K.; Strickland, A.L.; Castrillon, D.H.; Carrick, K.; Jiang, Q.; Niu, S.; Rivera-Colon, G.; Gwin, K.; Hinson, S.; et al. PD-L1 Expression and CD8+ Tumor-Infiltrating Lymphocytes in Different Types of Tubo-Ovarian Carcinoma and Their Prognostic Value in High-Grade Serous Carcinoma. Am. J. Surg. Pathol. 2020, 44, 1050–1060. [Google Scholar] [CrossRef]
  34. Liu, P.; Chen, R.; Zhang, X.; Fu, R.; Tao, L.; Jia, W. Combined PD-1/PD-L1 and Tumor-Infiltrating Immune Cells Redefined a Unique Molecular Subtype of High-Grade Serous Ovarian Carcinoma. BMC Genom. 2022, 23, 51. [Google Scholar] [CrossRef] [PubMed]
  35. Pujade-Lauraine, E.; Fujiwara, K.; Ledermann, J.A.; Oza, A.M.; Kristeleit, R.; Ray-Coquard, I.-L.; Richardson, G.E.; Sessa, C.; Yonemori, K.; Banerjee, S.; et al. Avelumab Alone or in Combination with Chemotherapy versus Chemotherapy Alone in Platinum-Resistant or Platinum-Refractory Ovarian Cancer (JAVELIN Ovarian 200): An Open-Label, Three-Arm, Randomised, Phase 3 Study. Lancet Oncol. 2021, 22, 1034–1046. [Google Scholar] [CrossRef]
  36. Moore, K.N.; Bookman, M.; Sehouli, J.; Miller, A.; Anderson, C.; Scambia, G.; Myers, T.; Taskiran, C.; Robison, K.; Mäenpää, J.; et al. Atezolizumab, Bevacizumab, and Chemotherapy for Newly Diagnosed Stage III or IV Ovarian Cancer: Placebo-Controlled Randomized Phase III Trial (IMagyn050/GOG 3015/ENGOT-OV39). J. Clin. Oncol. 2021, 39, 1842–1855. [Google Scholar] [CrossRef]
  37. Morse, C.B.; Toukatly, M.N.; Kilgore, M.R.; Agnew, K.J.; Bernards, S.S.; Norquist, B.M.; Pennington, K.P.; Garcia, R.L.; Liao, J.B.; Swisher, E.M. Tumor Infiltrating Lymphocytes and Homologous Recombination Deficiency Are Independently Associated with Improved Survival in Ovarian Carcinoma. Gynecol. Oncol. 2019, 153, 217–222. [Google Scholar] [CrossRef] [PubMed]
  38. Vázquez-García, I.; Uhlitz, F.; Ceglia, N.; Lim, J.L.P.; Wu, M.; Mohibullah, N.; Niyazov, J.; Ruiz, A.E.B.; Boehm, K.M.; Bojilova, V.; et al. Ovarian Cancer Mutational Processes Drive Site-Specific Immune Evasion. Nature 2022, 612, 778–786. [Google Scholar] [CrossRef] [PubMed]
  39. The Cancer Genome Atlas Research Network. Integrated Genomic Analyses of Ovarian Carcinoma. Nature 2011, 474, 609–615. [Google Scholar] [CrossRef] [Green Version]
  40. Candido-dos-Reis, F.J.; Song, H.; Goode, E.L.; Cunningham, J.M.; Fridley, B.L.; Larson, M.C.; Alsop, K.; Dicks, E.; Harrington, P.; Ramus, S.J.; et al. Germline Mutation in BRCA1 or BRCA2 and Ten-Year Survival for Women Diagnosed with Epithelial Ovarian Cancer. Clin. Cancer Res. 2015, 21, 652–657. [Google Scholar] [CrossRef] [Green Version]
  41. Kotsopoulos, J.; Rosen, B.; Fan, I.; Moody, J.; McLaughlin, J.R.; Risch, H.; May, T.; Sun, P.; Narod, S.A. Ten-Year Survival after Epithelial Ovarian Cancer Is Not Associated with BRCA Mutation Status. Gynecol. Oncol. 2016, 140, 42–47. [Google Scholar] [CrossRef]
  42. Cui, M.; Xia, Q.; Zhang, X.; Yan, W.; Meng, D.; Xie, S.; Shen, S.; Jin, H.; Wang, S. Development and Validation of a Tumor Mutation Burden-Related Immune Prognostic Signature for Ovarian Cancers. Front. Genet. 2022, 12, 688207. [Google Scholar] [CrossRef]
  43. Cristescu, R.; Aurora-Garg, D.; Albright, A.; Xu, L.; Liu, X.Q.; Loboda, A.; Lang, L.; Jin, F.; Rubin, E.H.; Snyder, A.; et al. Tumor Mutational Burden Predicts the Efficacy of Pembrolizumab Monotherapy: A Pan-Tumor Retrospective Analysis of Participants with Advanced Solid Tumors. J. Immunother. Cancer 2022, 10, e003091. [Google Scholar] [CrossRef]
  44. Lim, D.; Murali, R.; Murray, M.P.; Veras, E.; Park, K.J.; Soslow, R.A. Morphological and Immunohistochemical Reevaluation of Tumors Initially Diagnosed as Ovarian Endometrioid Carcinoma with Emphasis on High-Grade Tumors. Am. J. Surg. Pathol. 2016, 40, 302–312. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Leskela, S.; Romero, I.; Rosa-Rosa, J.M.; Caniego-Casas, T.; Cristobal, E.; Pérez-Mies, B.; Gutierrez-Pecharroman, A.; Santón, A.; Ojeda, B.; López-Reig, R.; et al. Molecular Heterogeneity of Endometrioid Ovarian Carcinoma: An Analysis of 166 Cases Using the Endometrial Cancer Subrogate Molecular Classification. Am. J. Surg. Pathol. 2020, 44, 982–990. [Google Scholar] [CrossRef] [PubMed]
  46. Leskela, S.; Romero, I.; Cristobal, E.; Pérez-Mies, B.; Rosa-Rosa, J.M.; Gutierrez-Pecharroman, A.; Caniego-Casas, T.; Santón, A.; Ojeda, B.; López-Reig, R.; et al. Mismatch Repair Deficiency in Ovarian Carcinoma: Frequency, Causes, and Consequences. Am. J. Surg. Pathol. 2020, 44, 649–656. [Google Scholar] [CrossRef] [PubMed]
Ijms 24 11183 g001 550
Figure 1. (A) Case with high iTILs CD8+. Inset: CD8 immunohistochemistry. (B) Case with high sTILs CD8+. Inset: CD8 immunohistochemistry. (C) Case with no CD8+ lymphocytes. Inset: CD8 immunohistochemistry. (D) Case with high iTILs CD4+. Inset: CD4 immunohistochemistry. (E) Case with high sTILs CD4+. Inset: CD4 immunohistochemistry. (F) Case with no CD4+ lymphocytes. Inset: CD4 immunohistochemistry. (G) PD-L1-positive case. Inset: PD-L1 immunohistochemistry. (H) PD-L1-negative case. Inset: PD-L1 immunohistochemistry. Scale bar 20 µm.
Figure 1. (A) Case with high iTILs CD8+. Inset: CD8 immunohistochemistry. (B) Case with high sTILs CD8+. Inset: CD8 immunohistochemistry. (C) Case with no CD8+ lymphocytes. Inset: CD8 immunohistochemistry. (D) Case with high iTILs CD4+. Inset: CD4 immunohistochemistry. (E) Case with high sTILs CD4+. Inset: CD4 immunohistochemistry. (F) Case with no CD4+ lymphocytes. Inset: CD4 immunohistochemistry. (G) PD-L1-positive case. Inset: PD-L1 immunohistochemistry. (H) PD-L1-negative case. Inset: PD-L1 immunohistochemistry. Scale bar 20 µm.
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Figure 2. Wilcoxon tests showing the association between TILs and PD-L1 expression. No (negative PD-L1), Yes (positive PD-L1).
Figure 2. Wilcoxon tests showing the association between TILs and PD-L1 expression. No (negative PD-L1), Yes (positive PD-L1).
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Figure 3. Kaplan–Meier estimate of overall survival for the whole cohort.
Figure 3. Kaplan–Meier estimate of overall survival for the whole cohort.
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Figure 4. Kaplan–Meier estimates of relapse-free survival according to age at diagnosis, iTILs CD4+, iTILs CD8+ and iTILs ratio.
Figure 4. Kaplan–Meier estimates of relapse-free survival according to age at diagnosis, iTILs CD4+, iTILs CD8+ and iTILs ratio.
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Figure 5. Kaplan–Meier estimates of overall survival, according to age at diagnosis, iTILs CD4+, iTILs CD8+ and iTILs ratio.
Figure 5. Kaplan–Meier estimates of overall survival, according to age at diagnosis, iTILs CD4+, iTILs CD8+ and iTILs ratio.
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Figure 6. Multivariate Cox model showing age, iTILs CD4+ (LITCD4_Level) and iTILs CD8+ (LITCD8_Level) as independent prognostic factors for overall survival. The asterisk indicates statistical significance: (*) p-value = 0.01 to 0.05 and (**) p-value < 0.01.
Figure 6. Multivariate Cox model showing age, iTILs CD4+ (LITCD4_Level) and iTILs CD8+ (LITCD8_Level) as independent prognostic factors for overall survival. The asterisk indicates statistical significance: (*) p-value = 0.01 to 0.05 and (**) p-value < 0.01.
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Table
Table 1. Features of our series.
Table 1. Features of our series.
Percentage
Age at diagnosis
n = 124median56
mean57
IQR49–64
FIGO stage
n = 124IA, IB2721.8
IC5947.6
IIA, IIB3830.6
PD-L1
n = 123Negative11391.9
Positive108.1
BRCA1
n = 69Wild type5884.1
Mutated1115.9
BRCA2
n = 69Wild type6391.3
Mutated68.7
TMB
n = 40median5.04
mean6.06
IQR3.4–6–7
Relapsed
n = 123Yes4435.8
No7964.2
Deceased
n = 123Yes2722
No9678
Table
Table 2. Summary statistics of TILs and proportion of TILs in each category for the whole series. Tumors with no (negative), moderate (1–20) and high (>20) TILs. iTIL, intraepithelial tumor-infiltrating lymphocytes; sTIL, stromal tumor-infiltrating lymphocytes.
Table 2. Summary statistics of TILs and proportion of TILs in each category for the whole series. Tumors with no (negative), moderate (1–20) and high (>20) TILs. iTIL, intraepithelial tumor-infiltrating lymphocytes; sTIL, stromal tumor-infiltrating lymphocytes.
MedianMeanIQRNegative1–20>20
iTIL CD4+55.950–285 (70.2%)23 (19%)13 (10.7%)
sTIL CD4+19.9180–25.541 (33.9%)50 (41.3%)30 (24.8%)
iTIL CD8+2649.66.9–65.315 (12.5%)32 (26.7%)73 (60.8%)
sTIL CD8+16.331.47.5–40.910 (8.3%)54 (45%)56 (46.7%)
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Pizarro, D.; Romero, I.; Pérez-Mies, B.; Redondo, A.; Caniego-Casas, T.; Carretero-Barrio, I.; Cristóbal, E.; Gutiérrez-Pecharromán, A.; Santaballa, A.; D’Angelo, E.; et al. The Prognostic Significance of Tumor-Infiltrating Lymphocytes, PD-L1, BRCA Mutation Status and Tumor Mutational Burden in Early-Stage High-Grade Serous Ovarian Carcinoma—A Study by the Spanish Group for Ovarian Cancer Research (GEICO). Int. J. Mol. Sci. 2023, 24, 11183. https://doi.org/10.3390/ijms241311183

AMA Style

Pizarro D, Romero I, Pérez-Mies B, Redondo A, Caniego-Casas T, Carretero-Barrio I, Cristóbal E, Gutiérrez-Pecharromán A, Santaballa A, D’Angelo E, et al. The Prognostic Significance of Tumor-Infiltrating Lymphocytes, PD-L1, BRCA Mutation Status and Tumor Mutational Burden in Early-Stage High-Grade Serous Ovarian Carcinoma—A Study by the Spanish Group for Ovarian Cancer Research (GEICO). International Journal of Molecular Sciences. 2023; 24(13):11183. https://doi.org/10.3390/ijms241311183

Chicago/Turabian Style

Pizarro, David, Ignacio Romero, Belén Pérez-Mies, Andrés Redondo, Tamara Caniego-Casas, Irene Carretero-Barrio, Eva Cristóbal, Ana Gutiérrez-Pecharromán, Ana Santaballa, Emanuela D’Angelo, and et al. 2023. "The Prognostic Significance of Tumor-Infiltrating Lymphocytes, PD-L1, BRCA Mutation Status and Tumor Mutational Burden in Early-Stage High-Grade Serous Ovarian Carcinoma—A Study by the Spanish Group for Ovarian Cancer Research (GEICO)" International Journal of Molecular Sciences 24, no. 13: 11183. https://doi.org/10.3390/ijms241311183

APA Style

Pizarro, D., Romero, I., Pérez-Mies, B., Redondo, A., Caniego-Casas, T., Carretero-Barrio, I., Cristóbal, E., Gutiérrez-Pecharromán, A., Santaballa, A., D’Angelo, E., Hardisson, D., Vieites, B., Matías-Guiu, X., Estévez, P., Guerra, E., Prat, J., Poveda, A., López-Guerrero, J. A., & Palacios, J. (2023). The Prognostic Significance of Tumor-Infiltrating Lymphocytes, PD-L1, BRCA Mutation Status and Tumor Mutational Burden in Early-Stage High-Grade Serous Ovarian Carcinoma—A Study by the Spanish Group for Ovarian Cancer Research (GEICO). International Journal of Molecular Sciences, 24(13), 11183. https://doi.org/10.3390/ijms241311183

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