Title: Evaluation of PINK1 Protein Expression as a Predictive Marker for the Efficacy of
Adjuvant Chemotherapy in Colorectal Cancer: A Retrospective Study
Version: 3 Date: 07 Jun 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
1. Limited Sample Size & Retrospective Design
Only 83 patients total and just 25 recurred, with only 11 RNA-seq samples (4 PINK1#High, 7
PINK1#Low).
The small size weakens statistical power, especially for multivariate models linking PINK1 to
survival.
2. Lack of Control Group (Surgery Alone)
All patients received adjuvant chemo—no non#chemo surgery control arm.
Without comparison to surgery#alone patients, it’s hard to determine if PINK1 predicts benefit
from chemotherapy or reflects prognosis.
3. Heterogeneous Chemotherapy Regimens
“Fluoropyrimidine#based” regimens varied among patients.
Treatment heterogeneity introduces a confounder—differences in outcome may be influenced
by regimen variability rather than PINK1 expression.
4. IHC Scoring Reliability Concerns
The scoring methodology combines subjective intensity + percentage scoring; inter-observer
variability is possible despite a pathologist’s confirmation.
Unlike H#Score validation in other studies (e.g., CRLM analysis) your scoring system isn't
benchmarked.
Lack of quantitative measures (e.g., digital image analysis) or inter-rater reproducibility metrics
could be flagged.
5. Lack of Functional Validation
The study is purely correlative—no in vitro or in vivo functional assays to demonstrate PINK1’s
direct effect on chemo#resistance.
Other research has shown PINK1’s mechanistic roles using cell lines and animal models. A
functional follow#up would greatly strengthen the link.
6. Protein vs mRNA Expression Discrepancy
A mismatch between PINK1 protein and mRNA levels is noted, but not deeply investigated.
Without assessing phosphorylated (activated) PINK1 or turnover rates (e.g., via PARL
cleavage), it remains unclear if IHC truly reflects functionally relevant protein.
7. Unclear Cut-Off Definition for High vs Low Expression
A score of 3–4 defines “high” but seems arbitrarily chosen without ROC analysis or validation
cohort.
Classification may vary across different labs or settings without an optimized or validated
threshold.
8. Potential Confounding Clinicopathologic Variables
While multivariate models adjust for differentiation, other potential variables (e.g., stage II vs III,
performance status, tumor site, microsatellite instability, KRAS/BRAF status) aren’t included.
Could PINK1 be a surrogate for these factors rather than an independent predictor?
9. Pathway & Enrichment Analyses Based on Limited RNA-seq Cases
GO/KEGG/GSEA findings are derived from only 11 samples, reducing confidence in identified
pathways (autophagy, amino acid transport).
Such analyses should ideally be validated in external or larger datasets.
10. Uncertain Clinical Usefulness
While PINK1 is proposed as a prognostic biomarker, the clinical actionability is unclear.
Does it guide decisions between fluoropyrimidine alone vs combined oxaliplatin, or indicate
patients who need autophagy inhibition?
Current clinical guidelines (NCCN, ESMO, ASCO) do not incorporate PINK1; prospective
validation is needed before clinical use.
Title: Evaluation of PINK1 Protein Expression as a Predictive Marker for the Efficacy of
Adjuvant Chemotherapy in Colorectal Cancer: A Retrospective Study
Version: 3 Date: 07 Jun 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
1. Limited Sample Size & Retrospective Design
Only 83 patients total and just 25 recurred, with only 11 RNA-seq samples (4 PINK1#High, 7
PINK1#Low).
The small size weakens statistical power, especially for multivariate models linking PINK1 to
survival.
2. Lack of Control Group (Surgery Alone)
All patients received adjuvant chemo—no non#chemo surgery control arm.
Without comparison to surgery#alone patients, it’s hard to determine if PINK1 predicts benefit
from chemotherapy or reflects prognosis.
3. Heterogeneous Chemotherapy Regimens
“Fluoropyrimidine#based” regimens varied among patients.
Treatment heterogeneity introduces a confounder—differences in outcome may be influenced
by regimen variability rather than PINK1 expression.
4. IHC Scoring Reliability Concerns
The scoring methodology combines subjective intensity + percentage scoring; inter-observer
variability is possible despite a pathologist’s confirmation.
Unlike H#Score validation in other studies (e.g., CRLM analysis) your scoring system isn't
benchmarked.
Lack of quantitative measures (e.g., digital image analysis) or inter-rater reproducibility metrics
could be flagged.
5. Lack of Functional Validation
The study is purely correlative—no in vitro or in vivo functional assays to demonstrate PINK1’s
direct effect on chemo#resistance.
Other research has shown PINK1’s mechanistic roles using cell lines and animal models. A
functional follow#up would greatly strengthen the link.
6. Protein vs mRNA Expression Discrepancy
A mismatch between PINK1 protein and mRNA levels is noted, but not deeply investigated.
Without assessing phosphorylated (activated) PINK1 or turnover rates (e.g., via PARL
cleavage), it remains unclear if IHC truly reflects functionally relevant protein.
7. Unclear Cut-Off Definition for High vs Low Expression
A score of 3–4 defines “high” but seems arbitrarily chosen without ROC analysis or validation
cohort.
Classification may vary across different labs or settings without an optimized or validated
threshold.
8. Potential Confounding Clinicopathologic Variables
While multivariate models adjust for differentiation, other potential variables (e.g., stage II vs III,
performance status, tumor site, microsatellite instability, KRAS/BRAF status) aren’t included.
Could PINK1 be a surrogate for these factors rather than an independent predictor?
9. Pathway & Enrichment Analyses Based on Limited RNA-seq Cases
GO/KEGG/GSEA findings are derived from only 11 samples, reducing confidence in identified
pathways (autophagy, amino acid transport).
Such analyses should ideally be validated in external or larger datasets.
10. Uncertain Clinical Usefulness
While PINK1 is proposed as a prognostic biomarker, the clinical actionability is unclear.
Does it guide decisions between fluoropyrimidine alone vs combined oxaliplatin, or indicate
patients who need autophagy inhibition?
Current clinical guidelines (NCCN, ESMO, ASCO) do not incorporate PINK1; prospective
validation is needed before clinical use.
Please review this paper.
user
Title: Evaluation of PINK1 Protein Expression as a Predictive Marker for the Efficacy of
Adjuvant Chemotherapy in Colorectal Cancer: A Retrospective Study
Version: 3 Date: 07 Jun 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
1. Limited Sample Size & Retrospective Design
Only 83 patients total and just 25 recurred, with only 11 RNA-seq samples (4 PINK1#High, 7
PINK1#Low).
The small size weakens statistical power, especially for multivariate models linking PINK1 to
survival.
2. Lack of Control Group (Surgery Alone)
All patients received adjuvant chemo—no non#chemo surgery control arm.
Without comparison to surgery#alone patients, it’s hard to determine if PINK1 predicts benefit
from chemotherapy or reflects prognosis.
3. Heterogeneous Chemotherapy Regimens
“Fluoropyrimidine#based” regimens varied among patients.
Treatment heterogeneity introduces a confounder—differences in outcome may be influenced
by regimen variability rather than PINK1 expression.
4. IHC Scoring Reliability Concerns
The scoring methodology combines subjective intensity + percentage scoring; inter-observer
variability is possible despite a pathologist’s confirmation.
Unlike H#Score validation in other studies (e.g., CRLM analysis) your scoring system isn't
benchmarked.
Lack of quantitative measures (e.g., digital image analysis) or inter-rater reproducibility metrics
could be flagged.
5. Lack of Functional Validation
The study is purely correlative—no in vitro or in vivo functional assays to demonstrate PINK1’s
direct effect on chemo#resistance.
Other research has shown PINK1’s mechanistic roles using cell lines and animal models. A
functional follow#up would greatly strengthen the link.
6. Protein vs mRNA Expression Discrepancy
A mismatch between PINK1 protein and mRNA levels is noted, but not deeply investigated.
Without assessing phosphorylated (activated) PINK1 or turnover rates (e.g., via PARL
cleavage), it remains unclear if IHC truly reflects functionally relevant protein.
7. Unclear Cut-Off Definition for High vs Low Expression
A score of 3–4 defines “high” but seems arbitrarily chosen without ROC analysis or validation
cohort.
Classification may vary across different labs or settings without an optimized or validated
threshold.
8. Potential Confounding Clinicopathologic Variables
While multivariate models adjust for differentiation, other potential variables (e.g., stage II vs III,
performance status, tumor site, microsatellite instability, KRAS/BRAF status) aren’t included.
Could PINK1 be a surrogate for these factors rather than an independent predictor?
9. Pathway & Enrichment Analyses Based on Limited RNA-seq Cases
GO/KEGG/GSEA findings are derived from only 11 samples, reducing confidence in identified
pathways (autophagy, amino acid transport).
Such analyses should ideally be validated in external or larger datasets.
10. Uncertain Clinical Usefulness
While PINK1 is proposed as a prognostic biomarker, the clinical actionability is unclear.
Does it guide decisions between fluoropyrimidine alone vs combined oxaliplatin, or indicate
patients who need autophagy inhibition?
Current clinical guidelines (NCCN, ESMO, ASCO) do not incorporate PINK1; prospective
validation is needed before clinical use.
assistant