Association Between Results of a Gene Expression Signature Assay and Recurrence-Free Interval in Patients With Stage II Colon Cancer in Cancer and Leukemia Group B 9581 (Alliance)

An invasion front gene expression signature for higher-risk patient selection in stage IIA MSS colon cancer

Stage II colon cancer (CC) encompasses a heterogeneous group of patients with diverse survival experiences: 87% to 58% 5-year relative survival rates for stages IIA and IIC, respectively. While stage IIA patients are usually spared the adjuvant chemotherapy, some of them relapse and may benefit from it; thus, their timely identification is crucial. Current gene expression signatures did not specifically target this group nor did they find their place in clinical practice. Since processes at invasion front have also been linked to tumor progression, we hypothesize that aside from bulk tumor features, focusing on the invasion front may provide additional clues for this stratification. A retrospective matched case-control collection of 39 stage IIA microsatellite-stable (MSS) untreated CCs was analyzed to identify prognostic gene expression-based signatures. The endpoint was defined as relapse within 5 years vs. no relapse for at least 6 years. From the same tumors, three different classifiers (bulk tumor, invasion front, and constrained baseline on bulk tumor) were developed and their performance estimated. The baseline classifier, while the weakest, was validated in two independent data sets. The best performing signature was based on invasion front profiles [area under the receiver operating curve (AUC) = 0.931 (0.815-1.0)] and contained genes associated with KRAS pathway activation, apical junction complex, and heme metabolism. Its combination with bulk tumor classifier further improved the accuracy of the predictions.

Unraveling the role of tumor sidedness in prognosis of stage II colon cancer

Background

Stage II colon cancer has varying risks for metastasis, and treatment strategies depend on molecular and clinicopathological features. While tumor-sidedness is a well-accepted prognostic factor for stage III/IV colon cancer, its role in stage II is controversial. Understanding its effect in stage II is crucial for improving treatment strategies.

Methods

We analyzed clinical and follow-up data of colon cancer from the Surveillance, Epidemiology, and End Results database (2004-2017). Patients were divided into a primary study cohort (2010-2017) and a validation cohort (2004-2009). The baseline characteristics between right-sided colon cancer (RCC) and left-sided colon cancer (LCC) groups were compared. Moreover, the effect of tumor size on cancer-specific survival (CSS) was evaluated using Kaplan-Meier analysis.

Results

The study involved 87,355 patients in the study cohort and 65,858 in the validation cohort. Of the study cohort, 52.3% were diagnosed with RCC. The median age was 64 years old, with 48.5% females and 76.8% of white people. In addition, stage II RCC showed better CSS compared with LCC (5-year CSS 88.0% vs 85.5%, P < 0.001), while stage III/IV RCC demonstrated poorer outcomes. Multivariate Cox regression analysis identified that the right-sidedness was a positive prognostic factor in stages I/II but negative in stages III (HR 1.10, P < 0.001) and IV (HR 1.26, P < 0.001). Chemotherapy rates decreased in RCC, particularly in stage II (RCC vs LCC: 16.2% vs 28.5%, P < 0.001). Subgroup analysis, stratified by T3/T4 stages and chemotherapy status, further highlighted better survival outcomes in RCC.

Conclusions

RCC is associated with a significantly better prognosis in stage II. The importance of considering tumor-sidedness in clinical decision-making and the design of future clinical trials should be emphasized.

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach

BACKGROUND

Accurate estimation of the long-term risk of recurrence in patients with non-metastatic colorectal cancer (CRC) is crucial for clinical management. Histology-based deep learning is expected to provide more abundant information for risk stratification.

METHODS

We developed and validated a weakly supervised deep-learning model for predicting 5-year relapse-free survival (RFS) to stratify patients with different risks based on histological images from three hospitals of 614 cases with non-metastatic CRC. A deep prognostic factor (DL-RRS) was established to stratify patients into high and low-risk group. The areas under the curve (AUCs) were calculated to evaluate the performances of models.

RESULTS

Our proposed model achieves the AUCs of 0.833 (95% CI: 0.736-0.905) and 0.715 (95% CI: 0.647-0.776) on validation cohort and external test cohort, respectively. The 5-year RFS rate was 45.7% for high DL-RRS patients, and 82.5% for low DL-RRS patients respectively in the external test cohort (HR: 3.89, 95% CI: 2.51-6.03, P < 0.001). Adjuvant chemotherapy was associated with improved RFS in Stage II patients with high DL-RRS (HR: 0.15, 95% CI: 0.06-0.38, P < 0.001).

CONCLUSIONS

DL-RRS has a good predictive performance of 5-year recurrence risk in CRC, and will better serve the clinical decision-making.

Unraveling a novel hippo-associated immunological prognostic signature: The contribution of SERPINE1 in facilitating colorectal cancer progression via the notch signaling pathway

BACKGROUND

Accumulating evidence demonstrated that Hippo signaling pathway is implicated in tumor initiation and progression. However, there have been limited studies on establishing signatures utilizing genes related to the Hippo pathway to evaluate prognosis and clinical efficacy in colorectal cancer (CRC) patients.

METHODS

Hippo pathway-associated genes with prognostic significance were identified in the TCGA database. Subsequently, a prognostic signature associated with the Hippo pathway was constructed using Cox and LASSO regression analyses. Survival analysis, ROC analysis, and stratified analyses were conducted to appraise the performance effect of our prognostic model. We also explored the relationship between the risk score and tumor immune microenvironment. Furthermore, GO analyses and GSEA were performed for SERPINE1. Additional experiments were conducted to illuminate the underlying function and possible mechanism of SERPINE1 in CRC cell proliferation and migration.

RESULTS

We identified 58 differentially expressed genes associated with Hippo pathway that have prognostic significance in CRC. Among them, five genes (PPP2CB, SERPINE1, WNT5A, TCF7L1, and LEF1) were selected to establish a prognostic signature for CRC. Multivariate analysis demonstrated that this signature exhibited excellent diagnostic and prognostic performance, providing maximum benefits for CRC patients. In accordance with the prognostic signatures, the cases were divided into low-risk and high-risk groups. Remarkably, the high-risk group displayed lower immune scores, reduced immune cell infiltration, and decreased expression of immune checkpoints. Low-risk group could more possibly benefit from conventional chemotherapeutic and targeted therapies. CRC exhibited significantly elevated expression of SERPINE1, which was linked to worst overall survival. Moreover, inhibition of SERPINE1 suppressed proliferation, invasion, and migration of CRC cells via Notch pathway.

CONCLUSIONS

To sum up, we established a novel immunological prognostic signature utilizing genes associated with the Hippo pathway. This signature offers accurate prognostic prediction and can guide individualized therapy for patients with CRC.

Enhanced Clinical Utility of Molecular Budding Signature as a Recurrence Risk Determinant in Stage II and III Colon Cancer Patients

BACKGROUND

A molecular budding signature (MBS), which consists of seven tumor budding-related genes, was recently presented as a prominent prognostic indicator in colon cancer (CC) using microarray data acquired from frozen specimens. This study aimed to confirm the predictive power of MBS for recurrence risk based on formalin-fixed, paraffin-embedded (FFPE) materials.

METHODS

This research utilized the same microarray data from a prior multicenter study using FFPE whole tissue sections, which retrospectively reviewed 232 stage II CC patients without adjuvant chemotherapy and 302 stage III CC patients with adjuvant chemotherapy. All patients underwent upfront curative surgery without neoadjuvant therapy between 2009 and 2012. An MBS score was calculated using the mean of log2 [each signal] of seven genes (MSLN, SLC4A11, WNT11, SCEL, RUNX2, MGAT3, and FOXC1) as described before.

RESULTS

The MBS-low group exhibited a better relapse-free survival (RFS) than the MBS-high group in stage II (P = 0.0077) and in stage III CC patients (P = 0.0003). Multivariate analyses revealed that the MBS score was an independent prognostic factor in both stage II (P = 0.0257) and stage III patients (P = 0.0022). Especially among T4, N2, or both (high-risk) stage III patients, the MBS-low group demonstrated markedly better RFS compared with the MBS-high group (P = 0.0013).

CONCLUSIONS

This study confirmed the predictive power of the MBS for recurrence risk by employing FFPE materials in stage II/III CC patients.

Opportunities on the horizon for the management of early colon cancer

There is a clear unmet need to improve early colon cancer management. This review encompasses the current systemic treatment landscape and summarises novel and pivotal trials. The Immunoscore and circulating tumour DNA (ctDNA) are studied to evaluate which patients should receive no, 3, or 6 months of adjuvant treatment. Several trials also test escalating treatment strategies for non-cleared ctDNA following standard adjuvant chemotherapy. Advances made in treating patients with metastatic colon cancer are now being translated to the early colon cancer setting. Two ongoing RCTs study immune checkpoint inhibitors (ICI) in patients with microsatellite instable high (MSI-H) early colon cancer as adjuvant treatment. Neo-adjuvant treatment is being studied in several ongoing RCTs as well. The complete response rate in patients with MSI-H tumours following ICI in neoadjuvant trials has potential organ-sparing implications.

Cost-effectiveness of precision molecular diagnostic tests for stage II colorectal cancer

Background

In colorectal cancer, inappropriate use of adjuvant chemotherapies may lead to significant increases in healthcare costs and harms to patients. Genome-based interventions are being increasingly used in the stratification of patients according to their risk profiles. However, earlier cost-effectiveness analyses of precision molecular diagnostics have indicated a paucity of data on comparative health economic outcomes. Our aim was to compare the cost-effectiveness of marketed genomic tests used in the prognosis of stage II colorectal cancer patients.

Methods

A Markov model was developed to compare the cost-effectiveness of treatment guided by any one of the following genomic tests: 12-gene assay or the 18-gene expression assay or the 482-gene signature or the Immunoscore assay in a hypothetical cohort of patients (n=1,000) with stage II colorectal cancer. Our study investigated outcomes in three health states: no recurrence, recurrence and death. This study was conducted from a societal perspective, and a 3% discount was applied to the costs and health outcomes. Sensitivity analyses were performed to assess the uncertainty of model parameters on the results.

Results

The cost of the Immunoscore assay strategy in stage II colorectal cancer patients was estimated to be US $23,564 with a gain of 3.903 quality-adjusted life years (QALYs) as compared with the 12-gene assay strategy at US $24,545 and 3.903 QALYs; the 18-gene assay strategy at US $28,374 and 3.623 QALYs; and the 482-gene signature treatment strategy at US $33,315 with 3.704 QALYs. Sensitivity analyses indicated that incremental cost-effectiveness ratio (ICER) values were sensitive to costs of genomic tests and adjuvant chemotherapies; and utilities related to patients in the no-recurrence health state.

Conclusions

Overall, the Immunoscore assay seems to be a dominant strategy at a threshold willingness-to-pay of $50,000 per QALY, but in the US other tests have been used for longer. Thus, the 12-gene assay may generate cost savings compared to the 18-gene expression assay. The findings of our study may provide useful information to policymakers regarding selection of the most appropriate genomic test, and resource allocation decisions.

SAMHD1 as a prognostic and predictive biomarker in stage II colorectal cancer: A multicenter cohort study

Background

The identification of high-risk population patients is key to the personalized treatment options for the stage II colorectal cancers. The use of proteomics in the prognosis of patients with stage II colorectal cancer remains unclear.

Methods

Using quantitative proteomics, we analyzed proteins that are differentially expressed in the tumor and adjacent normal tissues of 11 paired colorectal cancer patients with and without recurrence selected by a nested case-control design. Of the 21 identified proteins, we selected one candidate protein. The association of the corresponding gene of the selected protein with overall survival (OS) and adjuvant chemotherapy was analyzed using two independent cohorts of patients with stages II colorectal cancer.

Results

Sterile α motif and histidine-aspartate domain-containing protein 1 (SAMHD1) was selected as the candidate biomarker. A group of 124 patients (12.5%) were stratified into SAMHD1-high subgroup. The 5-year OS rate of SAMHD1-high patients was lower than that of SAMHD1-low patients with stage II colorectal cancer (discovery cohort: hazard ratio [HR] = 2.89, 95% confidence interval [CI], 1.17-7.18, P = 0.016; validation cohort: HR = 2.25, 95% CI, 1.17-4.34, P = 0.013). The Cox multivariate analysis yielded similar results. In a pooled database, the 5-year OS rate was significantly different between patients with and without adjuvant chemotherapy among stage II SAMHD1-low tumors than in patients with stage II SAMHD1-high tumors (88% vs. 77%, P = 0.032).

Conclusions

SAMHD1-high expression could help in identifying patients with stage II colorectal cancer with poor prognosis and less benefit from adjuvant chemotherapy.

Tumor Biomarker Testing for Metastatic Colorectal Cancer: a Canadian Consensus Practice Guideline

The systemic therapy management of metastatic colorectal cancer (mCRC) has evolved from primarily cytotoxic chemotherapies to now include targeted agents given alone or in combination with chemotherapy, and immune checkpoint inhibitors. A better understanding of the pathogenesis and molecular drivers of colorectal cancer not only aided the development of novel targeted therapies but led to the discovery of tumor mutations which act as predictive biomarkers for therapeutic response. Mutational status of the KRAS gene became the first genomic biomarker to be established as part of standard of care molecular testing, where KRAS mutations within exons 2, 3, and 4 predict a lack of response to anti- epidermal growth factor receptor therapies. Since then, several other biomarkers have become relevant to inform mCRC treatment; however, there are no published Canadian guidelines which reflect the current standards for biomarker testing. This guideline was developed by a pan-Canadian advisory group to provide contemporary, evidence-based recommendations on the minimum acceptable standards for biomarker testing in mCRC, and to describe additional biomarkers for consideration.

Evaluating the quality of the economic evidence in colorectal cancer genomics studies

The increase in the use of genome-based screening and diagnostic tests adds to the overall costs of oncologic care for colorectal cancer. This, in turn, has resulted in an increase in published economic analyses. Aim: To perform a systematic literature review of the available economic evidence evaluating the value of genomic testing for colorectal cancer and appraise the quality of the economic studies conducted to date. Methods: A systematic review of the literature for economic studies of colorectal cancer genomics from January 2006 through October 2020, and evaluation of study quality using the Quality of Health Economic Studies (QHES) instrument was conducted. The validated QHES was then applied to a final set of articles that met eligibility criteria. Results: Our search of the literature initially yielded 12,859 records. A final set of 49 articles met our inclusion criteria. The QHES score ranged from 24 to 100, with an average score of 82. Most of the studies (n = 40, 82%) scored above 75 and were considered of good quality. Conclusion: Our analysis revealed that most of the economic analyses of colorectal cancer genomic molecular diagnostics in the literature may be of good quality. There is, however, some variation in methodological rigor between the articles.

Combination of CDX2 H-score quantitative analysis with CD3 AI-guided analysis identifies patients with a good prognosis only in stage III colon cancer

AIM

Stratification of colon cancer (CC) of patients with stage II and III for risk of relapse is still needed especially to drive adjuvant therapy administration. Our study evaluates the prognostic performance of two known biomarkers, CDX2 and CD3, standalone or their combined information in stage II and III CC.

PATIENTS AND METHODS

CDX2 and CD3 expression was evaluated in Prodige-13 study gathering 443 stage II and 398 stage III primary CC on whole slide colectomy. We developed for this study an H-score to quantify CDX2 expression and used our artificial intelligence (AI)-guided tissue analysis ColoClass to detect CD3 in tumour core and invasive margin. Association between biomarkers and relapse-free survival was investigated.

RESULTS

Univariate analysis showed that the combined variable CD3-TC and CD3-IM was associated with prognosis in both stage II and stage III. CDX2, on the contrary, was associated with prognosis only in stage III. We subsequently associated CDX2 and combined immune parameters only in stage III. This multivariate analysis allowed us to distinguish a proportion of stage III CC harbouring a high CDX2 expression and a high immune infiltration with a particularly good prognosis compared to their counterpart.

CONCLUSION

This study validated the prognostic role of CDX2 and CD3 evaluated with immunohistochemistry procedures in stage III but not in stage II. This association would be conceivable in a routine pathology laboratory and could help oncologist to consider chemotherapy de-escalation for a part of stage III patients.

A Three-Genes Signature Predicting Colorectal Cancer Relapse Reveals LEMD1 Promoting CRC Cells Migration by RhoA/ROCK1 Signaling Pathway

Objective

Colorectal cancer (CRC) patients that experience early relapse consistently exhibit poor survival. However, no effective approach has been developed for the diagnosis and prognosis prediction of postoperative relapsed CRC.

Methods

Multiple datasets from the GEO database and TCGA database were utilized for bioinformatics analysis. WGCNA analyses and RRA analysis were performed to identify key genes. The COX/Lasso regression model was used to construct the recurrence model. Subsequent in vitro experiments further validated the potential role of the hub genes in CRC.

Results

A comprehensive analysis was performed on multiple CRC datasets and a CRC recurrence model was constructed containing LEMD1, SERPINE1, and SIAE. After further validation in two independent databases, we selected LEMD1 for in vitro experiments and found that LEMD1 could regulate CRC cell proliferation, migration, invasion, and promote EMT transition. The Rho-GTPase pulldown experiments further indicated that LEMD1 could affect RhoA activity and regulate cytoskeletal dynamics. Finally, we demonstrated that LEMD1 promoted CRC cell migration through the RhoA/ROCK1 signaling pathway.

Conclusions

In this study, a CRC relapse model consisting of LEMD1, SERPINE1, and SIAE was constructed by comprehensive analysis of multiple CRC datasets. LEMD1 could promote CRC cell migration through the RhoA/ROCK signaling pathway.

Updates in the Treatment of Patients With Colorectal Cancer

A number of assays are now available to estimate the prognosis of early-stage colorectal cancer, including multigene assays, the Immunoscore, and circulating tumor DNA (ctDNA). Although the results of these assays may provide prognostic information regarding the risk for recurrence, their use as a predictive assay has not yet been validated. Therefore, although these assays may be useful for prognostication, further validation would be required to include in the NCCN Guidelines. For the treatment of metastatic colorectal cancer, major advances have included the use of checkpoint inhibition in metastatic disease. Studies are currently underway to further define their optimal use.

Sustainable Clinical Development of Adjuvant Chemotherapy for Colon Cancer

Numerous clinical studies in an adjuvant setting have been conducted and the combination therapy of 5-fluorouracil and oxaliplatin has been established as the standard treatment for Stage III and as an option for high-risk Stage II patients. Biologics such as bevacizumab and antiepidermal growth factor receptor antibodies have failed to show additional survival benefits. The indication of adjuvant chemotherapy has been determined according to the pathological stage. Nevertheless, a pathological diagnosis does not necessarily result in selection of the optimal treatment. To improve treatment decisions, many trials have aimed to stratify patients into treatment groups using genomic testing. Recently, gene signature, Immunoscore, and circulating tumor DNA (ctDNA) assays have been reported and among them, ctDNA was shown to be a promising accurate predictive marker for recurrence. Treatment of ctDNA-positive patients with aggressive chemotherapy may reduce recurrence rates. The ultimate goal is to accurately predict the risk of recurrence and to prevent recurrence in colon cancer patients. In this review we focus on the clinical development of adjuvant chemotherapy and stratification of patients according to risk of recurrence and the future direction of adjuvant chemotherapy.

Pan-Asian adapted ESMO Clinical Practice Guidelines for the diagnosis treatment and follow-up of patients with localised colon cancer

The most recent version of the European Society for Medical Oncology (ESMO) Clinical Practice Guidelines for the diagnosis, treatment and follow-up of localised colon cancer was published in 2020. It was decided by both the ESMO and the Japanese Society of Medical Oncology (JSMO) to convene a special virtual guidelines meeting in March 2021 to adapt the ESMO 2020 guidelines to take into account the ethnic differences associated with the treatment of localised colon cancer in Asian patients. These guidelines represent the consensus opinions reached by experts in the treatment of patients with localised colon cancer representing the oncological societies of Japan (JSMO), China (CSCO), India (ISMPO), Korea (KSMO), Malaysia (MOS), Singapore (SSO) and Taiwan (TOS). The voting was based on scientific evidence and was independent of the current treatment practices and drug availability and reimbursement situations in the different Asian countries.

Evaluation of Clinical and Pathological Factors to Predict High Risk of Recurrence in Patients With Stage II Colon Cancer

BACKGROUND

The ability to predict patients with stage II colon cancer at high risk of recurrence is currently limited to certain clinicopathologic factors.

PATIENTS AND METHODS

This population-based study reviewed various prognostic factors to identify those associated with worse time to recurrence (TTR) and improved disease-specific survival (DSS), and to subsequently develop a prognostic index (PI) to identify high risk cancers.

RESULTS

Multivariate analyses revealed factors significant for TTR and DSS. A PI derived from the TTR risk factors identified 3 risk groups using 5-year rate without relapse: 88% for low-risk, 81% for intermediate-risk, and 59% for high risk.

CONCLUSION

This model was better at identifying high risk patients than using equally weighted standard risk factors.

A tumor microenvironment-related mRNA-ncRNA signature for prediction early relapse and chemotherapeutic sensitivity in early-stage lung adenocarcinoma

OBJECTIVES

Postoperative early relapse of early-stage lung adenocarcinoma is implicated in poor prognosis. The purpose of our study was to develop an integrated mRNA and non-coding RNA (ncRNA) signature to identify patients at high risk of early relapse in stage I-II lung adenocarcinoma who underwent complete resection.

METHODS

Early-stage lung adenocarcinoma data from Gene Expression Omnibus database were divided into training set and testing set. Propensity score matching analysis was performed between patients in early relapse group and long-term nonrelapse group from training set. Transcriptome analysis, random survival forest and LASSO Cox regression model were used to build an early relapse-related multigene signature. The robustness of the signature was evaluated in testing set and RNA-Seq dataset from The Cancer Genome Atlas (TCGA). The chemotherapy sensitivity, tumor microenvironment and mutation landscape related to the signature were explored using bioinformatics analysis.

RESULTS

Twelve mRNAs and one ncRNA were selected. The multigene signature achieved a strong power for early relapse prediction in training set (HR 3.19, 95% CI 2.16-4.72, P < 0.001) and testing set (HR 2.91, 95% CI 1.63-5.20, P = 0.002). Decision curve analyses revealed that the signature had a good clinical usefulness. Groups divided by the signature exhibited different chemotherapy sensitivity, tumor microenvironment characteristics and mutation landscapes.

CONCLUSIONS

Our results indicated that the integrated mRNA-ncRNA signature may be an innovative biomarker to predict early relapse of early-stage lung adenocarcinoma, and may provide more effective treatment strategies.

How I treat stage II colon cancer patients

Stage II colon cancer (CC) is probably one of the best prognosis gastrointestinal tumors seen in our consultations, but often takes a lot of time for physicians to determine appropriate treatment because of the limited benefit of adjuvant chemotherapy (CT) in these patients, together with the limited evidence in this situation. How to choose the best treatment for each individual patient is thus dependent on molecular (microsatellite instability/microsatellite stability status) and clinico-pathological features relevant enough to classify these tumors into low-, intermediate- and high-risk stage II disease and to choose an appropriate attitude for each of these subgroups. In practice, the first step in treatment decision making must be to assess the patient's status and comorbidities to see if the patient is eligible for an adjuvant treatment. Then, as fluoropyrimidines (FPs) are the corner stone of CC adjuvant treatment, screening for dihydropyrimidine dehydrogenase deficiency is mandatory in western countries. Finally, depending on the patient's characteristics and tumor risk stage, the strategy may be surveillance, adjuvant FP alone or oxaliplatin-based adjuvant CT. In the near future, new tools such as Immunoscore® (HalioDx; Luminy Biotech Enterprises, Marseille Cedex, France) and circulating tumor DNA may help to identify more precisely patients with minimal residual disease for more personalized adjuvant treatment approaches.

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Stage II CC is a heterogeneous disease with a complex management due to the limited data and benefit of adjuvant CT.

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Risk stratification through prognostic parameters is crucial to aid clinicians in determining the appropriate therapy.

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Lymph node sampling <12 and pT4 are currently recognized as the major prognostic features associated with worse survival.

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Adjuvant CT should be considered by incorporating prognostic features and balanced against patient's age and comorbidities.

Integrated approaches for precision oncology in colorectal cancer: The more you know, the better

Colorectal cancer (CRC) is one of the most common human malignancies accounting for approximately 10 % of worldwide cancer incidence and mortality. While early-stage CRC is mainly a preventable and curable disease, metastatic colorectal cancer (mCRC) remains an unmet clinical need. Moreover, about 25 % of CRC cases are diagnosed only at the metastatic stage. Despite the extensive molecular and functional knowledge on this disease, systemic therapy for mCRC still relies on traditional 5-fluorouracil (5-FU)-based chemotherapy regimens. On the other hand, targeted therapies and immunotherapy have shown effectiveness only in a limited subset of patients. For these reasons, there is a growing need to define the molecular and biological landscape of individual patients to implement novel, rationally driven, tailored therapies. In this review, we explore current and emerging approaches for CRC management such as genomic, transcriptomic and metabolomic analysis, the use of liquid biopsies and the implementation of patients' preclinical avatars. In particular, we discuss the contribution of each of these tools in elucidating patient specific features, with the aim of improving our ability in advancing the diagnosis and treatment of colorectal tumors.

Prognostic Cancer Gene Expression Signatures: Current Status and Challenges

Current staging systems of cancer are mainly based on the anatomical extent of disease. They need refinement by biological parameters to improve stratification of patients for tumor therapy or surveillance strategies. Thanks to developments in genomic, transcriptomic, and big-data technologies, we are now able to explore molecular characteristics of tumors in detail and determine their clinical relevance. This has led to numerous prognostic and predictive gene expression signatures that have the potential to establish a classification of tumor subgroups by biological determinants. However, only a few gene signatures have reached the stage of clinical implementation so far. In this review article, we summarize the current status, and present and future challenges of prognostic gene signatures in three relevant cancer entities: breast cancer, colorectal cancer, and hepatocellular carcinoma.

Use of Circulating Cell-Free DNA to Guide Precision Medicine in Patients with Colorectal Cancer

Patient-specific biomarkers form the foundation of precision medicine strategies. To realize the promise of precision medicine in patients with colorectal cancer (CRC), access to cost-effective, convenient, and safe assays is critical. Improvements in diagnostic technology have enabled ultrasensitive and specific assays to identify cell-free DNA (cfDNA) from a routine blood draw. Clinicians are already employing these minimally invasive assays to identify drivers of therapeutic resistance and measure genomic heterogeneity, particularly when tumor tissue is difficult to access or serial sampling is necessary. As cfDNA diagnostic technology continues to improve, more innovative applications are anticipated. In this review, we focus on four clinical applications for cfDNA analysis in the management of CRC: detecting minimal residual disease, monitoring treatment response in the metastatic setting, identifying drivers of treatment sensitivity and resistance, and guiding therapeutic strategies to overcome resistance.

ctDNA and Adjuvant Therapy for Colorectal Cancer: Time to Re-Invent Our Treatment Paradigm

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. While there have been significant developments in the treatments for patients with metastatic CRC in recent years, improving outcomes in the adjuvant setting has been more challenging. Recent technological advances in circulating tumour DNA (ctDNA) assay with the ability to detect minimal residual disease (MRD) after curative intent surgery will fundamentally change how we assess recurrence risk and conduct adjuvant trials. Studies in non-metastatic CRC have now demonstrated the prognostic impact of ctDNA analysis after curative intent surgery over and above current standard of care clinicopathological criteria. This ability of ctDNA analysis to stratify patients into low- and very-high-risk groups provides a window of opportunity to personalise adjuvant treatment where escalation/de-escalation of adjuvant systemic therapy could potentially increase cure rates and also reduce treatment-related physical and financial toxicity. Emerging data suggest that conversion of ctDNA from detectable to undetectable after adjuvant chemotherapy may reflect treatment efficacy. This real-time assessment of treatment benefit could be used as a surrogate endpoint for adjuvant novel drug development. Several ctDNA-based randomized adjuvant trials are ongoing internationally to confirm the clinical utility of ctDNA in colorectal cancer.

[Update of the recommendations for the determination of biomarkers in colorectal carcinoma. National Consensus of the Spanish Society of Medical Oncology and the Spanish Society of Pathology]

This update of the consensus of the Spanish Society of Medical Oncology (Sociedad Española de Oncología Médica - SEOM) and the Spanish Society of Pathology (Sociedad Española de Anatomía Patológica - SEAP), reviews the advances in the analysis of biomarkers in advanced colorectal cancer (CRC) as well as susceptibility markers of hereditary CRC and molecular biomarkers of localized CRC. Recently published information on the essential determination of KRAS, NRAS and BRAF mutations and the possible benefits of determining the amplification of human epidermal growth factor receptor 2 (HER2), the expression of proteins in the DNA repair pathway and the study of NTRK fusions are also evaluated. From a pathological point of view, the importance of analysing the tumour budding and poorly differentiated clusters and its prognostic value in CRC is reviewed, as well as the impact of molecular lymph node analysis on lymph node staging in CRC. The incorporation of pan-genomic technologies, such as next-generation sequencing (NGS) and liquid biopsy in the clinical management of patients with CRC is also outlined. All these aspects are developed in this guide which, like the previous one, will be revised when necessary in the future.

Update of the recommendations for the determination of biomarkers in colorectal carcinoma: National Consensus of the Spanish Society of Medical Oncology and the Spanish Society of Pathology

In this update of the consensus of the Spanish Society of Medical Oncology (Sociedad Española de Oncología Médica—SEOM) and the Spanish Society of Pathology (Sociedad Española de Anatomía Patológica—SEAP), advances in the analysis of biomarkers in advanced colorectal cancer (CRC) as well as susceptibility markers of hereditary CRC and molecular biomarkers of localized CRC are reviewed. Recently published information on the essential determination of KRAS, NRAS and BRAF mutations and the convenience of determining the amplification of human epidermal growth factor receptor 2 (HER2), the expression of proteins in the DNA repair pathway and the study of NTRK fusions are also evaluated. From the pathological point of view, the importance of analysing the tumour budding and poorly differentiated clusters, and its prognostic value in CRC is reviewed, as well as the impact of molecular lymph node analysis on lymph node staging in CRC. The incorporation of pan-genomic technologies, such as next-generation sequencing (NGS) and liquid biopsy in the clinical management of patients with CRC is also outlined. All these aspects are developed in this guide, which, like the previous one, will remain open to any necessary revision in the future.

A Validation Study for Recurrence Risk Stratification of Stage II Colon Cancer Using the 55-Gene Classifier

INTRODUCTION

DNA microarrays, such as the consensus molecular subtype (CMS) classification using >600 genes, are used to predict cancer patient prognosis. We recently constructed a simple 55-gene classifier (55GC) system to risk stratify colon cancer (CC).

OBJECTIVE

Here, we validate the 55GC specifically for stage II CC and compare it with CMS categories.

METHODS

Tissue sections from 232 stage II CC patients who underwent curative surgery without adjuvant chemotherapy between 2009 and 2012 were subjected to DNA microarray analysis.

RESULTS

Based on the 55GC, patients were classified into microsatellite instability-like (27%), chromosomal instability-like (41%), and stromal (32%) subtypes with 5-year relapse-free survival (RFS) rates of 88.5, 83.3, and 71.2%, respectively (stromal vs. others: p = 0.0049). Multivariate analysis by Cox's proportional hazard model revealed that the stromal subtype, pT4, and the number of lymph nodes examined (<12) were independent poor prognostic factors. The overall concordance rate between 55GC and CMS was 72%, and 5-year RFS rates of patients with CMS1, CMS2, CMS3, and CMS4 cancers were 100, 85.5, 92.3, and 73.0%, respectively (p = 0.0113).

CONCLUSIONS

We conclude that the 55GC is a useful and reproducible grading system for stage II CC recurrence risk stratification.

Genomic profiling in oncology clinical practice

The development of high-throughput technologies such as next-generation sequencing for DNA sequencing together with the decrease in their cost has led to the progressive introduction of genomic profiling in our daily practice in oncology. Nowadays, genomic profiling is part of genetic counseling, cancer diagnosis, molecular characterization, and as a biomarker of prognosis and response to treatment. Furthermore, germline or somatic genomic characterization of the tumor may provide new treatment opportunities for patients with cancer. In this review, we will summarize the clinical applications and limitations of genomic profiling in oncology clinical practice, focusing on next-generation sequencing.

Challenges and solutions in patient treatment strategies for stage II colon cancer

Colorectal cancer remains one of the most common cancers worldwide and, despite improvements in treatment options for late-stage metastatic cancer, there are still questions surrounding how best to treat early-stage disease patients. Some recent advances have been made in the staging of cancer and improving the risk assessment of strategies for patient treatment. A number of high-risk features have been proposed that may help to stratify stage II cancer patients into groups that will truly benefit from adjuvant chemotherapy. Diagnostic tests are becoming available to measure these biomarkers, utilizing both currently available and novel technologies. This review will describe the challenges in treatment decisions for early-stage colon cancer and how personalized medicine can assist clinicians in making the best treatment choices for patients with stage II colon cancer in particular.

Classification of a DNA Microarray for Diagnosing Cancer Using a Complex Network Based Method

Applications that classify DNA microarray expression data are helpful for diagnosing cancer. Many attempts have been made to analyze these data; however, new methods are needed to obtain better results. In this study, a Complex Network (CN) classifier was exploited to implement the classification task. An algorithm was used to initialize the structure, which allowed input variables to be selected over layered connections and different activation functions for different nodes. Then, a hybrid method integrated the Genetic Programming and the Particle Swarm Optimization algorithms was used to identify an optimal structure with the parameters encoded in the classifier. The single CN classifier and an ensemble of CN classifiers were tested on four bench data sets. To ensure diversity of the ensemble classifiers, we constructed a base classifier using different feature sets, i.e., Pearson's correlation, Spearman's correlation, Euclidean distance, Cosine coefficient and the Fisher-ratio. The experimental results suggest that a single classifier can be used to obtain state-of-the-art results and the ensemble yielded better results.

Noninferiority of three months versus six months of oxaliplatin-based adjuvant chemotherapy for resected colon cancer. How should IDEA findings affect clinical practice?

The eagerly awaited results of the multi-continental International Duration Evaluation of Adjuvant Chemotherapy (IDEA) project have recently been presented at major oncological meetings. The 3-year disease-free survival (DFS) was presented for 12,834 Stage III colon cancer patients in a pooled analysis of 6 individual noninferiority phase III randomized trials, all investigating three versus six months of oxaliplatin-based adjuvant therapy. Noninferiority (NI) could not be demonstrated for the whole population as the DFS hazard ratio (HR) of 1.07 with its 95% CI of 1.00-1.15 crossed the postulated NI boundary of 1.12. However, there was an expected reduction in the incidence of specific side effects with the three months treatment. NI could be demonstrated for the T3N1 subgroup (∼60% of patients, HR for DFS 1.01, 95% CI 0.90-1.12). Moreover, NI was also declared for the subgroup treated with the CAPOX regimen (capecitabine plus oxaliplatin, ∼40% of patients), but the CAPOX choice was physician-based and not subject to randomization. Overall, the IDEA results indicate that three months of therapy might be adequate for most of Stage III tumors; however, a small subset of these patients still have high risk of recurrence and death with short treatment duration. Precise predictors of benefit need to be identified, nonetheless tumor-intrinsic factors, such as tumor stage, might currently be considered as useful tools to inform the decision-making process.

Back to the future: routine morphological assessment of the tumour microenvironment is prognostic in stage II/III colon cancer in a large population-based study

AIMS

Both morphological and molecular approaches have highlighted the biological and prognostic importance of the tumour microenvironment in colorectal cancer (CRC). Despite this, microscopic assessment of the tumour microenvironment has not been adopted into routine practice. The study aim was to identify those tumour microenvironmental features that are most likely to provide prognostic information and be feasible to use in routine pathology reporting practice.

METHODS AND RESULTS

On the basis of existing evidence, we selected specific morphological features relating to peritumoral inflammatory and stromal responses, agreed criteria for scoring, and assessed these in representative haematoxylin and eosin (H&E)-stained whole tumour sections from a population-based cohort of 445 stage II/III colon cancer cases. Moderate/severe peritumoral diffuse lymphoid inflammation and Crohn's disease-like reaction were associated with significantly reduced risks of CRC-specific death [adjusted hazard ratio (HR) 0.48, 95% confidence interval (CI) 0.31-0.76, and HR 0.60, 95% CI 0.42-0.84, respectively]. The presence of >50% tumour stromal percentage, as assessed by global evaluation of tumour area, was associated with a significantly increased risk of CRC-specific death (HR 1.60 95% CI 1.06-2.41). A composite 'fibroinflammatory score' (0-3), combining dichotomized scores of these three features, showed a highly significant association with survival outcomes. Those with a score of ≥2 had an almost 2.5-fold increased risk of CRC-specific death (HR 2.44, 95% CI 1.56-3.81) as compared with those scoring zero. These associations were stronger in microsatellite instability (MSI)-high tumours, potentially identifying a subset of MSI-high colon cancers that lack characteristic morphological features and have an associated worse prognosis.

CONCLUSIONS

In summary, reporting on H&E staining of selected microscopic features of the tumour microenvironment, independently or in combination, offers valuable prognostic information in stage II/III colon cancer, and may allow morphological correlation with developing molecular classifications of prognostic and predictive relevance.

What We Know About Stage II and III Colon Cancer: It's Still Not Enough

The introduction of oxaliplatin as adjuvant treatment for stage III colon cancer in 2004 has been the last practice changing progress in adjuvant treatment for patients with early colon cancer. Since then, many prognostic and predictive biomarkers have been studied, but only DNA mismatch repair status has been validated as having an important prognostic value. Accordingly, TNM and clinical-pathological patterns, such as pT4 lesions and lymph node sampling <12 nodes, are the main factors that guide physicians' choice regarding adjuvant treatment. More recently, many biomarkers showed promising results: POLE, ErbB2, CDX2, SMAD4, BRAF and KRAS. In addition to these, immune-contexture, molecular classification, and gene signatures could become new ways to better classify colon cancer patients with more discriminatory power than TNM. The aim of this review is to report the state-of-the-art of prognostic and predictive factors in the adjuvant setting and which of these could modify clinical practice and maybe replace TNM classification.

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH.

Tumour expression profiling is currently used for prognostic and predictive purposes without taking into account the intra patient heterogeneity. Here the authors show that cancer cell specific signatures overcome the tumour heterogeneity effect and result in better classification of colorectal cancer patients.

Standardising RNA profiling based biomarker application in cancer-The need for robust control of technical variables

Histopathology-based staging of colorectal cancer (CRC) has utility in assessing the prognosis of patient subtypes, but as yet cannot accurately predict individual patient's treatment response. Transcriptomics approaches, using array based or next generation sequencing (NGS) platforms, of formalin fixed paraffin embedded tissue can be harnessed to develop multi-gene biomarkers for predicting both prognosis and treatment response, leading to stratification of treatment. While transcriptomics can shape future biomarker development, currently <1% of published biomarkers become clinically validated tests, often due to poor study design or lack of independent validation. In this review of a large number of CRC transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNA transcripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers.

Development of a novel prognostic signature of long non-coding RNAs in lung adenocarcinoma

OBJECTIVES

Increasing evidence suggests that long non-coding RNAs (lncRNAs) may play a crucial role in many biological processes in a variety of cancers and serve as the basis for many clinical applications including prognostic biomarkers and potential therapeutic targets. The aim of this study is to develop a prognostic lncRNA signature with RNA-seq data in lung adenocarcinomas.

METHODS

LncRNA expression profiles and clinical data of lung adenocarcinoma patients from The Cancer Genome Atlas (TCGA) were analyzed. Univariate Cox proportional regression model was used to identify prognostic lncRNAs, and then multivariate Cox proportional regression model was used to develop a prognostic signature. Survivals were compared using log-rank test, and the biological implications of prognostic lncRNAs were analyzed using the KEGG pathway functional enrichment analysis.

RESULTS

We identified eight lncRNAs which had prognostic association with p value <0.01 in a TCGA lung adenocarcinoma cohort of 478 patients. Then a novel prognostic signature with the eight lncRNAs was developed using Cox regression model. Signature high-risk cases had worse overall survival (OS, median 85.97 vs. 38.34 months, p < 0.001) and disease-free survival (DFS, median 44.02 vs. 26.58 months, p = 0.007) than low-risk cases. Multivariate Cox regression analysis suggested that the eight-lncRNA signature was independent of clinical and pathological factors. KEGG pathway functional enrichment analysis indicated potential functional roles of the eight prognostic lncRNAs in tumorigenesis.

CONCLUSIONS

Our findings suggest that the eight-lncRNA signature might provide an effective independent prognostic model for the prediction of lung adenocarcinoma patients.