Comprehensive Profiling of Gene Copy Number Alterations Predicts Patient Prognosis in Resected Stages I-III Lung Adenocarcinoma

A pan-cancer analysis of the oncogenic role of Golgi transport 1B in human tumors

Background

Owing to the aggressiveness and treatment-refractory nature of cancer, ideal candidates for early diagnosis and treatment are needed. Golgi transport 1B (GOLT1B) has been associated with cellular malignant behaviors and immune responses in colorectal and lung cancer, but a systematic pan-cancer analysis on GOLT1B has not been conducted.

Methods

The expression status and clinical association of GOLT1B in The Cancer Genome Atlas (TCGA) were analyzed. Genetic and methylation alterations in GOLT1B were explored. The relationship between GOLT1B and immune cell infiltration was also investigated. Genes related to GOLT1B expression were selected and analyzed.

Results

GOLT1B was highly expressed in most tumors, and there was a positive correlation between GOLT1B expression and clinical pathological parameters. High expression levels of GOLT1B have been associated with poor prognosis of most cancers. Copy number amplification was the primary type of GOLT1B genetic alterations, which was related to the prognosis of pan-cancer cases. There were different levels of GOLT1B promoter methylation across cancer types. The methylation level of the probe cg07371838 and cg25816357 was closely associated with prognosis in diverse cancers. There was also a positive correlation between GOLT1B genetic alterations and CD4+ T lymphocytes, especially the Th2 subset, as well as between GOLT1B expression and the estimated infiltration value of cancer-associated fibroblasts. Serine/threonine kinase receptor-associated protein (STRAP), integrator complex subunit 13 (INTS13), and ethanolamine kinase 1 (ETNK1) were the most relevant genes for GOLT1B expression, and their interactions with GOLT1B were involved in regulating the transforming growth factor (TGF)-β receptor signaling pathway and epithelial-mesenchymal transition (EMT).

Conclusions

This pan-cancer analysis provided a comprehensive understanding of the oncogenic role of GOLT1B, highlighting a potential mechanism whereby GOLT1B influences the tumor microenvironment, as well as cancer immunotherapy.

Assessment of MYC and TERT copy number variations in lung cancer using digital PCR

OBJECTIVE

Lung cancer is the second most frequent cancer type and the most common cause of cancer-related deaths worldwide. Alteration of gene copy numbers are associated with lung cancer and the determination of copy number variations (CNV) is appropriate for the discrimination between tumor and non-tumor tissue in lung cancer. As telomerase reverse transcriptase (TERT) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) play a role in lung cancer the aims of this study were the verification of our recent results analyzing MYC CNV in tumor and non-tumor tissue of lung cancer patients using an independent study group and the assessment of TERT CNV as an additional marker.

RESULTS

TERT and MYC status was analyzed using digital PCR (dPCR) in tumor and adjacent non-tumor tissue samples of 114 lung cancer patients. The difference between tumor and non-tumor samples were statistically significant (p < 0.0001) for TERT and MYC. Using a predefined specificity of 99% a sensitivity of 41% and 51% was observed for TERT and MYC, respectively. For the combination of TERT and MYC the overall sensitivity increased to 60% at 99% specificity. We demonstrated that a combination of markers increases the performance in comparison to individual markers. Additionally, the determination of CNV using dPCR might be an appropriate tool in precision medicine.

Single-cell RNA sequencing reveals distinct tumor microenvironment of ground glass nodules and solid nodules in lung adenocarcinoma

Introduction: Lung adenocarcinoma (LUAD) is the most prevalent lung cancer. LUAD presents as ground glass nodules (GGN) and solid nodules (SN) in imaging studies. GGN is an early type of LUAD with good prognosis. However, SN exhibits a more malignant behavior than GGN, including worse pathological staging and tumor prognosis. The mechanism leading to the different malignancy levels of GGN and SN remains elusive. Methods: Three patients with GGN and three patients with SN diagnosed with early LUAD were enrolled. The tumor samples were digested to a single-cell suspension and analyzed using 10× Genomic Single-cell ribonucleic acid sequences (scRNA-seq) techniques. Results: A total of 15,902 cells were obtained and classified into nine major types. The tumor microenvironment (TME) was subsequently described in detail. ScRNA-seq revealed that ribosome-related pathways and cell adhesion played similar but distinct roles in the two groups. SN also had more active cell proliferation, enriched cell cycle regulatory pathways, and severe inflammatory responses. Conclusion: We observed changes in the cellular composition and transcriptomic profile of GGN and SN. The study improved the understanding of the underlying mechanisms of lung carcinogenesis and contributed to lung cancer prevention and treatment.

Potential Association of Cytochrome P450 Copy Number Alteration in Tumour with Chemotherapy Resistance in Lung Adenocarcinoma Patients

Resistance to anticancer agents is a major obstacle to efficacious tumour therapy and responsible for high cancer-related mortality rates. Some resistance mechanisms are associated with pharmacokinetic variability in anticancer drug exposure due to genetic polymorphisms of drug-metabolizing cytochrome P450 (CYP) enzymes, whereas variations in tumoural metabolism as a consequence of CYP copy number alterations are assumed to contribute to the selection of resistant cells. A high-throughput quantitative polymerase chain reaction (qPCR)-based method was developed for detection of CYP copy number alterations in tumours, and a scoring system improved the identification of inappropriate reference genes that underwent deletion/multiplication in tumours. The copy numbers of both the target (CYP2C8, CYP3A4) and the reference genes (ALB, B2M, BCKDHA, F5, CD36, MPO, TBP, RPPH1) established in primary lung adenocarcinoma by the qPCR-based method were congruent with those determined by next-generation sequencing (for 10 genes, slope = 0.9498, r2 = 0.72). In treatment naïve adenocarcinoma samples, the copy number multiplication of paclitaxel-metabolizing CYP2C8 and/or CYP3A4 was more prevalent in non-responder patients with progressive disease/exit than in responders with complete remission. The high-throughput qPCR-based method can become an alternative approach to next-generation sequencing in routine clinical practice, and identification of altered CYP copy numbers may provide a promising biomarker for therapy-resistant tumours.

Whole-exome mutational landscape and molecular marker study in mucinous and clear cell ovarian cancer cell lines 3AO and ES2

BACKGROUND

Ovarian cancer is one of the most lethal cancers in women because it is often diagnosed at an advanced stage. The molecular markers investigated thus far have been unsatisfactory.

METHODS

We performed whole-exome sequencing on the human ovarian cancer cell lines 3AO and ES2 and the normal ovarian epithelial cell line IOSE-80. Molecular markers of ovarian cancer were screened from shared mutation genes and copy number variation genes in the 6q21-qter region.

RESULTS

We found that missense mutations were the most common mutations in the gene (93%). The MUC12, FLG and MUC16 genes were highly mutated in 3AO and ES2 cells. Copy number amplification occurred mainly in 4p16.1 and 11q14.3, and copy number deletions occurred in 4q34.3 and 18p11.21. A total of 23 hub genes were screened, of which 16 were closely related to the survival of ovarian cancer patients. The three genes CCDC170, THBS2 and COL14A1 are most significantly correlated with the survival and prognosis of ovarian cancer. In particular, the overall survival of ovarian cancer patients with high CCDC170 gene expression was significantly prolonged (P < 0.001). The expression of CCDC170 in normal tissues was significantly higher than that in ovarian cancer tissues (P < 0.05), and its expression was significantly decreased in advanced ovarian cancer. Western blotting and immunofluorescence assays also showed that the expression of CCDC170 in ovarian cancer cells was significantly lower than that in normal cells (P < 0.001, P < 0.01).

CONCLUSIONS

CCDC170 is expected to become a new diagnostic molecular target and prognostic indicator for ovarian cancer patients, which can provide new ideas for the design of antitumor drugs.

Somatic mutation but not aneuploidy differentiates lung cancer in never-smokers and smokers

Lung cancer in never-smokers disproportionately affects older women. To understand the mutational landscape of this cohort, we performed detailed genome characterization of 73 lung adenocarcinomas from participants of the Women’s Health Initiative (WHI). We find enrichment of EGFR mutations in never-/light-smokers and KRAS mutations in heavy smokers as expected, but we also show that the specific variants of these genes differ by smoking status, with important therapeutic implications. Mutational signature analysis revealed signatures of clock, APOBEC, and DNA repair deficiency in never-/light-smokers; however, the mutational load of these signatures did not differ significantly from those found in smokers. Last, tumors from both smokers and never-/light-smokers shared copy number subtypes, with no significant differences in aneuploidy. Thus, the genomic landscape of lung cancer in never-/light-smokers and smokers is predominantly differentiated by somatic mutations and not copy number alterations.

Artificial intelligence-based non-small cell lung cancer transcriptome RNA-sequence analysis technology selection guide

The incidence and mortality rates of lung cancer are high worldwide, where non-small cell lung cancer (NSCLC) accounts for more than 85% of lung cancer cases. Recent non-small cell lung cancer research has been focused on analyzing patient prognosis after surgery and identifying mechanisms in connection with clinical cohort and ribonucleic acid (RNA) sequencing data, including single-cell ribonucleic acid (scRNA) sequencing data. This paper investigates statistical techniques and artificial intelligence (AI) based non-small cell lung cancer transcriptome data analysis methods divided into target and analysis technology groups. The methodologies of transcriptome data were schematically categorized so researchers can easily match analysis methods according to their goals. The most widely known and frequently utilized transcriptome analysis goal is to find essential biomarkers and classify carcinomas and cluster NSCLC subtypes. Transcriptome analysis methods are divided into three major categories: Statistical analysis, machine learning, and deep learning. Specific models and ensemble techniques typically used in NSCLC analysis are summarized in this paper, with the intent to lay a foundation for advanced research by converging and linking the various analysis methods available.

Crosstalk between ROCK1 and PYROXD1 regulates CAFs activation and promotes laryngeal squamous cell carcinoma metastasis

We previously found that the Rho-associated kinase 1 (ROCK1) activated Cancer-associated fibroblasts (CAFs) to promote LSCC metastasis. Accumulating evidence indicates that pyridine nucleotide-disulfide oxidoreductase domain 1 (PYROXD1) is an oncogene; however, the crosstalk between ROCK1 and PYROXD1 in LSCC metastasis remains largely unknown. Here, we found that ROCK1 could target PYROXD1. The knockdown of ROCK1 expression reduces the expression of PYROXD1, while the knockdown of PYROXD1 expression did not alter the expression of ROCK1 indicating that ROCK1 is upstream of PYROXD1. Further, LSCC cells cocultured with PYROXD1 knocked-down CAFs exhibited lower proliferation, migration, invasion and metastasis abilities. Conversely, LSCC cells cocultured with PYROXD1-overexpressing CAFs showed opposite results. In conclusion, the crosstalk between ROCK1 and PYROXD1 regulated CAFs activation and promoted LSCC metastasis.

Genomic copy number alterations as biomarkers for triple negative pregnancy-associated breast cancer

Background

PABC, commonly defined as breast cancer diagnosed during or ≤ 1 year after pregnancy, accounts for 7% of all breast cancers in women ≤ 45 years. Compared to age-matched non-PABC patients, PABC is characterized by a particularly aggressive histopathologic profile with poorly differentiated and estrogen- and progesterone receptor negative tumors and associated high mortality rates. This study assessed the genomic background of triple-negative PABC tumors by detection of copy number alterations (CNAs).

Methods

MLPA was used to compare CNAs in breast cancer-associated chromosomal loci between triple-negative PABC- and subtype-matched non-PABC patients. Both CNA patterns were evaluated by cluster analysis; associations between individual gene CNAs, pathological characteristics and survival were explored.

Results

Triple-negative PABC tumors exhibited unique CNAs compared to non-PABC tumors, including enrichment for TOP2A copy number loss, an independent predictor of worse overall survival (HR 8.96, p = 0.020). Cluster analysis based on CNA profiles identified a triple-negative PABC-subgroup with a particularly poor prognosis, characterized by chromosome 8p copy number loss. Individual gene CNAs analysis revealed that FGFR1 copy number loss on chromosome 8p11.23 was an independent predictor of poor outcome in multivariate analysis (HR 3.59, p = 0.053) and predicted the development of distant metastases (p = 0.048).

Conclusion

This study provides novel insights into the biology of triple-negative PABC tumors suggesting that CNAs, particularly 8p loss and TOP2A loss, are involved in the development of breast cancer during pregnancy. FGFR1 loss and TOP2A loss seem to be promising new biomarkers that independently identify subgroups of PABC patients with poor prognosis. These genomic biomarkers may provide clues for personalized therapy.

Bilayer Forming Phospholipids as Targets for Cancer Therapy

Phospholipids represent a crucial component for the structure of cell membranes. Phosphatidylcholine and phosphatidylethanolamine are two phospholipids that comprise the majority of cell membranes. De novo biosynthesis of phosphatidylcholine and phosphatidylethanolamine occurs via the Kennedy pathway, and perturbations in the regulation of this pathway are linked to a variety of human diseases, including cancer. Altered phosphatidylcholine and phosphatidylethanolamine membrane content, phospholipid metabolite levels, and fatty acid profiles are frequently identified as hallmarks of cancer development and progression. This review summarizes the research on how phospholipid metabolism changes over oncogenic transformation, and how phospholipid profiling can differentiate between human cancer and healthy tissues, with a focus on colorectal cancer, breast cancer, and non-small cell lung cancer. The potential for phospholipids to serve as biomarkers for diagnostics, or as anticancer therapy targets, is also discussed.

Consensus for HER2 alterations testing in non-small-cell lung cancer

Human epidermal growth factor receptor 2 (HER2) is a transmembrane glycoprotein receptor with intracellular tyrosine kinase activity. Its alterations, including mutation, amplification and overexpression, could result in oncogenic potential and have been detected in many cancers such as non-small-cell lung cancer (NSCLC). Such alterations are, in general, considered markers of poor prognosis. Anti-HER2 antibody-drug conjugates, e.g. trastuzumab deruxtecan (T-DXd, DS-8201) and disitamab vedotin (RC48), were recently approved for HER2-positive breast and gastric cancers. Meanwhile, several HER2-targeted drugs, such as T-DXd, neratinib, afatinib, poziotinib and pyrotinib, have been evaluated in patients with advanced NSCLC, with several of them demonstrating clinical benefit. Therefore, identifying HER2 alterations is pivotal for NSCLC patients to benefit from these targeted therapies. Recent guidelines on HER2 testing were developed for breast and gastric cancer, however, and have not been fully established for NSCLC. The expert group here reached a consensus on HER2 alteration testing in NSCLC with the focus on clinicopathologic characteristics, therapies, detection methods and diagnostic criteria for HER2-altered NSCLC patients. We hope this consensus could improve the clinical management of NSCLC patients with HER2 alterations.

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Human epidermal growth factor receptor 2 (HER2) alterations lead to poor prognosis in non-small-cell lung cancer (NSCLC).

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Identifying HER2 alterations is pivotal to guide the anti-HER2-targeted therapies in NSCLC.

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The requirements for HER2 mutation, amplification or expression testing are distinct in NSCLC.

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This consensus fills the gap in the criteria for HER2 alteration testing in NSCLC.

Multi-Omics Analyses Revealed GOLT1B as a Potential Prognostic Gene in Breast Cancer Probably Regulating the Immune Microenvironment

As recently reported by The International Agency for Research on Cancer (IARC), breast cancer has the highest incidence of all cancers in 2020. Many studies have revealed that golgi apparatus is closely associated with the development of breast cancer. However, the role of golgi apparatus in immune microenvironment is still not clear. In this study, using RNA-Seq datasets of breast cancer patients from the public database (n = 1080), we revealed that GOLT1B, encoding a golgi vesicle transporter protein, was significantly higher expressed in human breast cancer tissues versus normal tissues. Besides, we verified GOLT1B expression in five breast cancer cell line using our original data and found GOLT1B was significantly up-regulated in MDA-MB-231, MCF-7, SKBR3. Subsequently, we identified GOLT1B as a potential independent prognostic factor for breast cancer. After a multi-omics analysis, we uncovered that the higher expression of GOLT1B in breast cancer tissues versus normal tissues might be due to the amplification of GOLT1B and altered phosphorylation of its potential transcriptional factors, including JUN and SIN3A. Subsequently, we discovered that GOLT1B potentially regulated the immune microenvironment basing on the finding that its expression was closely related to the tumor microenvironment score and infiltration of immune cells. Moreover, we revealed that GOLT1B might affect the overall survival rates of breast cancer through regulating the immune cell infiltration. Finally, we disclosed the potential pathways involved in the functions of GOLT1B in breast cancer, including metabolism and ECM-receptor interaction pathways. To sum up, we identified GOLT1B as a potential prognostic gene for breast cancer and disclosed its role in regulating the immune microenvironment.

Molecular charcterization of lung adenocarcinoma combining whole exome sequencing, copy number analysis and gene expression profiling

INTRODUCTION

Lung cancer is the leading cause of cancer mortality worldwide; lung adenocarcinoma (LUAD) corresponds to about 40% of lung cancers. LUAD is a genetically heterogeneous disease and the definition of this heterogeneity is of fundamental importance for prognosis and treatment.

AREAS COVERED

Based on primary literature, this review provides an updated analysis of multiomics studies based on the study of mutation profiling, copy number alterations and gene expression allowing for definition of molecular subgroups, prognostic factors based on molecular biomarkers, and identification of therapeutic targets. The authors sum up by providing the reader with their expert opinion on the potentialities of multiomics analysis of LUADs.

EXPERT OPINION

A detailed and comprehensive study of the co-occurring genetic abnormalities characterizing different LUAD subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of LUADs may provide a fundamental contribution to improve the survival of LUAD patients.

Analysis of Genome-Wide Alternative Splicing Profiling and Development of Potential Drugs in Lung Adenocarcinoma

Alternative splicing (AS) is significantly related to tumor development as well as a patient’s clinical characteristics. This study was designed to systematically analyze the survival-associated AS signatures in Lung adenocarcinoma (LUAD). Among 30,735 AS events in 9,635 genes, we found that there were 1,429 AS in 1,125 genes which were conspicuously related to the overall survival of LUAD patients. Then, according to the seven types of AS events, we established AS signatures and constructed a new combined prognostic model. The Kaplan-Meier curve results showed that seven types of AS signatures and the combined prognostic model could divide patients into distinct prognoses. The ROC curve shows that all eight AS signatures had powerful predictive properties with different AUCs ranging from 0.708 to 0.849. Additionally, the elevated risk scores were positively related to higher TNM stage and metastasis. Interestingly, AS events and splicing factors (SFs) network shed light on a meaningful connection between prognostic AS genes and corresponding SFs. Moreover, we found that the combined prognostic model signature has a higher predictive ability than the mRNA signature. Furthermore, tumors at high risk might evade immune recognition by decreasing the expression of antigen presentation genes. Finally, we predicted the three most significant small molecule drugs to inhibit LUAD. Among them, NVP-AUY922 had the lowest IC50 value and might become a potential drug to prolong a patient’s survival. In conclusion, our study established a potential prognostic signature for LUAD patients, revealed a splicing network between AS and SFs and possible immune escape mechanism, and provided several small-molecule drugs to inhibit tumorigenesis.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors

BACKGROUND

Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes.

METHODS

Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data.

RESULTS

The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes.

CONCLUSIONS

The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Phospholipid dynamics in ex vivo lung cancer and normal lung explants

In cancer cells, metabolic pathways are reprogrammed to promote cell proliferation and growth. While the rewiring of central biosynthetic pathways is being extensively studied, the dynamics of phospholipids in cancer cells are still poorly understood. In our study, we sought to evaluate de novo biosynthesis of glycerophospholipids (GPLs) in ex vivo lung cancer explants and corresponding normal lung tissue from six patients by utilizing a stable isotopic labeling approach. Incorporation of fully ¹³C-labeled glucose into the backbone of phosphatidylethanolamine (PE), phosphatidylcholine (PC), and phosphatidylinositol (PI) was analyzed by liquid chromatography/mass spectrometry. Lung cancer tissue showed significantly elevated isotopic enrichment within the glycerol backbone of PE, normalized to its incorporation into PI, compared to that in normal lung tissue; however, the size of the PE pool normalized to the size of the PI pool was smaller in tumor tissue. These findings indicate enhanced PE turnover in lung cancer tissue. Elevated biosynthesis of PE in lung cancer tissue was supported by enhanced expression of the PE biosynthesis genes ETNK2 and EPT1 and decreased expression of the PC and PI biosynthesis genes CHPT1 and CDS2, respectively, in different subtypes of lung cancer in publicly available datasets. Our study demonstrates that incorporation of glucose-derived carbons into the glycerol backbone of GPLs can be monitored to study phospholipid dynamics in tumor explants and shows that PE turnover is elevated in lung cancer tissue compared to normal lung tissue.

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With increasing mortality figures, the accurate prediction of prognosis has become essential. In recent years, multi-omics analysis has emerged as a useful survival prediction tool. However, the methodology relevant to multi-omics analysis has not yet been fully established and further improvements are required for clinical applications. In this study, we developed a novel method to accurately predict the survival of patients with lung cancer using multi-omics data. With unsupervised learning techniques, survival-associated subtypes in non-small cell lung cancer were first detected using the multi-omics datasets from six categories in The Cancer Genome Atlas (TCGA). The new subtypes, referred to as integration survival subtypes, clearly divided patients into longer and shorter-surviving groups (log-rank test: p = 0.003) and we confirmed that this is independent of histopathological classification (Chi-square test of independence: p = 0.94). Next, an attempt was made to detect the integration survival subtypes using only one categorical dataset. Our machine learning model that was only trained on the reverse phase protein array (RPPA) could accurately predict the integration survival subtypes (AUC = 0.99). The predicted subtypes could also distinguish between high and low risk patients (log-rank test: p = 0.012). Overall, this study explores novel potentials of multi-omics analysis to accurately predict the prognosis of patients with lung cancer.

Copy Number Alterations of Depressed Colorectal Neoplasm Predict the Survival and Response to Oxaliplatin in Proximal Colon Cancer

Depressed colorectal neoplasm exhibits high malignant potential and shows rapid invasiveness. We investigated the genomic profile of depressed neoplasms and clarified the survival outcome and treatment response of the cancers arising from them. We examined 20 depressed and 13 polypoid neoplasms by genome-wide copy number analysis. Subsequently, we validated the identified copy number alterations (CNAs) in an independent cohort of 37 depressed and 42 polypoid neoplasms. Finally, the CNAs were tested as biomarkers in 530 colorectal cancers (CRCs) to clarify the clinical outcome of depressed neoplasms. CNAs in MYC, CCNA1, and BIRC7 were significantly enriched in depressed neoplasms and designated as the D-marker panel. CRCs with a D-marker panel have significantly shorter progression-free survival compared with those without (p = 0.012), especially in stage I (p = 0.049), stages T₁₊₂ (p = 0.027), and proximal cancers (p = 0.002). The positivity of the D-marker panel was an independent risk factor of cancer progression (hazard ratio (95% confidence interval) = 1.52 (1.09–2.11)). Furthermore, the proximal CRCs with D-marker panels had worse overall and progression-free survival when taking oxaliplatin as chemotherapy than those that did not. The D-marker panel may help to optimize treatment and surveillance in proximal CRC and develop a molecular test. However, the current result remains preliminary, and further validation in prospective trials is warranted in the future.