NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer

Round 1

Reviewer 1 Report (Previous Reviewer 1)

In this manuscript the authors used NMR-based metabolomics to characterize the plasma metabolic profiles of NSCLC patients at different time points from the surgical removal of the tumour. In my opinion, with respect to the previous submission, the manuscripts has been modified but the overall quality of the manuscript is not significantly improved.

Below, some comments to improve the quality of the results:

-The metabolites analysis was performed on variables with the highest VIP-values. One single variable may contain several metabolites; thus the overall behaviour may be the average among the different metabolites. Metabolites analysis should be performed on the integral (or deconvolution) of the single metabolite signals.  Moreover, a biological interpretation of the observed changes should be added to the discussion.

- When high number of samples are available, on the assumption that metabolite concentrations are not normally distributed, non-parametric tests, such as the Wilcoxon–Mann–Whitney test, should be used. Multiple testing corrections, such as FDR, should be used to avoid false positive.  

-Please provide the p-value for the permutation test.

-It would be also of high interest to see if the metabolomic profiles of the patients with recurrence after six months that have been excluded from the analysis were significantly different from those of the patients with no recurrence.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 2)

The authors made rebuttals and responses to the comments appropriately. Congratulations .

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report (Previous Reviewer 1)

The authors modified the manuscript by introducing many experimental details. The weakness remains the lack of patient follow-up data. Despite this, I think that the manuscript can be published in cancers.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

In this manuscript the authors used NMR-based metabolomics to characterize the plasma metabolic profiles of NSCLC patients at different time points from the surgical removal of the tumour. The lack of follow-up data of the patients represents the main critical point. In my opinion, in the present form the manuscript is not acceptable for publication and the reported results should be implemented and improved.  

Hereafter some comments to improve the manuscript.

-Introduction:

Line 68-69: the meaning of this sentence is not clear. Please re-phrase it.

Line 77-78: As the authors correctly stated in the text, disease onset could introduce significant perturbation of the individual metabolomic fingerprint. But, the original individual metabolome could be restored when the pathological situation is over. Thus, the individual metabolomic fingerprint can be used to monitor disease onset but also to follow the individual response to a given treatment. This latter aspect is missing in the text.

Line 80: “Detection of such significant changes in the personal metabolite profile”…. What such significant changes are referred to?

Line 83-84. “Prediction of a patient's therapy response can improve patient stratification during treatment follow-up”. The authors should provide some examples showing how NMR-based metabolomics has been successfully used in this field. See for example (Cancers 2020, 12(12), 3574; https://doi.org/10.3390/cancers12123574).

“The correct selection of patients who would benefit from targeting minimal residual disease (MRD) by adjuvant chemotherapy could lower the disease recurrence rate and improve NSCLC outcome”. Has been NMR-based metabolomics used to this aim? If yes, please provide references.

“This study aims to determine the effect on the metabolite profile of early-stage NSCLC patients treated by complete surgical removal by prospectively collecting blood samples at specific pre-and postoperative time points. It has been reported that the metabolite profile is patient-specific and changes in the function of an acute stress response. However, the level of metabolic changes after removing a chronic stress condition, and thus after surgical resection of lung cancer, is currently unknown.” Does the study aim to determine the effect of the surgical removal on the metabolomic profiles of early-stage NSCLC patients? If yes, the sentence is not well formulated, please rephrase it.

 Materials and Methods:

“Within 8 hours after collection, blood samples were centrifuged for 15 minutes at 1600x g, and plasma aliquots of 400 µL were stored at -80°C until the proton (1H)-NMR analysis.” The pre-analytical procedures are very important for the reliability and the accuracy of the metabolomic analysis (ISO standard has been published on this topic, ISO 23118:2021). 8 hours is a very long-time frame in-between sample collection and processing. And how the samples have been conserved in during this time? The presence of cellular activity during the time between blood collection and processing to obtain plasma or serum, has been proposed as a major source of alterations. In particular, in vitro erythrocyte activity changes the levels of important metabolites, such as glucose and lactate. To minimize alterations, serum and plasma preparation should be initiated as soon as possible (within 30 min- max 2 hours) after blood collection (see N Biotechnol. 2022; 68:37-47. Doi: 10.1016/j.nbt.2022.01.006; Clin Chem. 2021;67(8):1153-1155. doi: 10.1093/clinchem/hvab092.).

Results:

The authors describe, by the use of multivariate analysis, that the individual profiles of the subjects significantly change after the surgery. But this finding is not surprising and the description is very general. The authors should provide a more detailed description of the metabolomic changes induced by the surgery. What are the metabolites that are significantly changed after the surgery? Are the changes common for all the subjects or there are some individual changes? How this information could be used for the prediction of a patient's therapy response? and to improve patient stratification during treatment follow-up?.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

First, As your defined early stage NSCLC (stage I-IIIA)in your paper, I suggest you to use the term of locally-advanced stage.

Second, one limitation of the study is the current lack of data from patients with NSCLC 353 recurrence after surgical resection.

could you explain the reason of this incomplete data collection in your prospective study?

Third, regarding the common predictors for recurrence, such as tumor grade, subtype, STAS, neurovascular invasion…etc. Can you provide such kind of data for comparison.

Fourth, operative data for curative resection of stage I-IIIA lung cancer should be presented, as this datas correlate to disease recurrence/outcome substantially.

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Interesting work, however i need more infos
regarding the NMR experiments setup before recommending this for publication 

1) why NMR over Mass spec ?

2) Which kind of NMR probe used for this exp? 

3) Please re-write your method part its not clear

4)Explain the usage of plasma samples over tissue 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The quality of the manuscript has not been substantially improved. Thus, in my opinion, in the present form the manuscript is not acceptable for publication.

Reviewer 3 Report

Unfortunately, you didn't answer my questions properly many things still unclear:

1) Please clarify the usage of Plasma samples in means of sample preparation and how you could cope with water signal which method were used!

section 2.3: For me what you wrote is not enough and acutely not clear as far as I understood you took the plasma samples after storage and just measured? 

How you did the quantification since it's not clear still for me? all these critical steps may highly influence/change the results