Microarray-based prediction of tumor response to neoadjuvant radiochemotherapy of patients with locally advanced rectal cancer

Predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer with two step feature selection and ensemble learning

Patients with locally advanced rectal cancer (LARC) show substantial individual variability and a pronounced imbalance in response distribution to neoadjuvant chemoradiotherapy (nCRT), posing significant challenges to treatment response prediction. This study aims to identify effective predictive biomarkers and develop an ensemble learning-based prediction model to assess the response of LARC patients to nCRT. A two-step feature selection method was developed to identify predictive biomarkers by deriving stable reversal gene pairs through within-sample relative expression orderings (REOs) from LARC patients undergoing nCRT. Preliminary screening utilized four methods-MDFS, Boruta, MCFS, and VSOLassoBag-to form a candidate feature set. Secondary screening ranked these features by permutation importance, applying Incremental Feature Selection (IFS) with an Extreme Gradient Boosting (XGBoost) to determine final predictive gene pairs. The ensemble model BoostForest, combining boosting and bagging, served as the predictive framework, with SHAP employed for interpretability. Through two-step feature selection, the 32-gene pair signature (32-GPS) was established as the final predictive biomarker. In the test set, the model achieved an area under the precision-recall curve (AUPRC) of 0.983 and an accuracy of 0.988. In the validation cohort, the AUPRC was 0.785, with an accuracy of 0.898, indicating strong model performance. The study further demonstrated that BoostForest achieved superior overall performance compared to Random Forest, Support Vector Machine (SVM), and XGBoost. To evaluate the effectiveness of the 32-GPS, its performance was compared with two alternative feature sets: the lasso-gene pair signature (lasso-GPS), derived through lasso regression, and the 15-shared gene pair signature (15-SGPS), consisting of gene pairs identified by all four feature selection methods. The 32-GPS demonstrated superior performance in both comparisons. The two-step feature selection method identified robust predictive biomarkers, and BoostForest outperformed Random Forest, Support Vector Machine, and XGBoost in classification performance and predictive capability.

Daxx Variation as a Potential Predictive Marker of the Therapeutic Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

OBJECTIVE

The response to neoadjuvant chemoradiotherapy (NACRT) for locally advanced rectal cancer (LARC) varies from achieving a complete pathological response to encountering resistance to treatment. Therefore, biomarkers for predicting the NACRT responses should be identified. This prospective study aimed to identify key genomic biomarkers as the predictors of the NACRT response with LARC.

METHODS

Overall, 67 patients with LARC treated with NACRT and proctectomy were divided into two groups based on the tumor regression grade (TRG) for identifying key biomarkers. Patients with a TRG of 0 or 1 were assigned to the sensitive response group, and patients with a TRG of 2 or 3 were the resistant response group. Twenty-nine postsurgical tumor samples were collected for whole exome sequencing (WES) to identify genomic variation biomarkers. The other 38 pairs of tumor specimens from pretreatment and postsurgery samples were evaluated by immunohistochemistry (IHC) to examine the biomarker features.

RESULTS

In the WES subcohort, 11 genes showed copy number variation, including FNKBIA, ARID1A, CCND2, CDK4, LYN, MDM2, RAD51B, RARA, SPEN, STAT3, and Daxx, which has the highest copy number variation. For the IHC subcohort, Daxx was initially highly expressed in the nuclei of tumor cells, particularly in the sensitive response group, while varying its expression after NACRT, demonstrating that Daxx levels were related to treatment responses and the survival benefit, especially a better disease-free survival (DFS).

CONCLUSION

We identified multiple genomic variations between sensitive and resistant responders and verified that Daxx is a potential predictive biomarker of the response to NACRT in LARC.

Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors

BACKGROUND

It is uncertain which biological features underpin the response of rectal cancer (RC) to radiotherapy. No biomarker is currently in clinical use to select patients for treatment modifications.

METHODS

We identified two cohorts of patients (total N = 249) with RC treated with neoadjuvant radiotherapy (45Gy/25) plus fluoropyrimidine. This discovery set included 57 cases with pathological complete response (pCR) to chemoradiotherapy (23%). Pre-treatment cancer biopsies were assessed using transcriptome-wide mRNA expression and targeted DNA sequencing for copy number and driver mutations. Biological candidate and machine learning (ML) approaches were used to identify predictors of pCR to radiotherapy independent of tumour stage. Findings were assessed in 107 cases from an independent validation set (GSE87211).

FINDINGS

Three gene expression sets showed significant independent associations with pCR: Fibroblast-TGFβ Response Signature (F-TBRS) with radioresistance; and cytotoxic lymphocyte (CL) expression signature and consensus molecular subtype CMS1 with radiosensitivity. These associations were replicated in the validation cohort. In parallel, a gradient boosting machine model comprising the expression of 33 genes generated in the discovery cohort showed high performance in GSE87211 with 90% sensitivity, 86% specificity. Biological and ML signatures indicated similar mechanisms underlying radiation response, and showed better AUC and p-values than published transcriptomic signatures of radiation response in RC.

INTERPRETATION

RCs responding completely to chemoradiotherapy (CRT) have biological characteristics of immune response and absence of immune inhibitory TGFβ signalling. These tumours may be identified with a potential biomarker based on a 33 gene expression signature. This could help select patients likely to respond to treatment with a primary radiotherapy approach as for anal cancer. Conversely, those with predicted radioresistance may be candidates for clinical trials evaluating addition of immune-oncology agents and stromal TGFβ signalling inhibition.

FUNDING

The Stratification in Colorectal Cancer Consortium (S:CORT) was funded by the Medical Research Council and Cancer Research UK (MR/M016587/1).

Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module. Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes. In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.

Delayed TME Surgery in a Watch-and-Wait Strategy After Neoadjuvant Chemoradiotherapy for Rectal Cancer: An Analysis of Hospital Costs and Surgical and Oncological Outcomes

BACKGROUND

A watch-and-wait strategy for patients with rectal cancer with a clinical complete response after neoadjuvant chemoradiotherapy is a valuable alternative for rectal resection. However, there are patients who will have residual tumor or regrowth during watch and wait.

OBJECTIVE

The aim of this study was to investigate safety and costs for patients who underwent delayed surgery after neoadjuvant chemoradiotherapy.

DESIGN

This is a retrospective cohort study with prospectively collected data.

SETTINGS

The study was conducted at a large teaching hospital.

PATIENTS

Between January 2015 and May 2020, 622 new rectal cancer patients were seen, of whom 200 received neoadjuvant chemoradiotherapy. Ninety-four patients were included, 65 of whom underwent immediate surgery and 29 of whom required delayed surgery after an initial watch-and-wait approach.

MAIN OUTCOME MEASURES

Outcome measures included 30-day postoperative morbidity rate, hospital costs. 2-year overall and disease-free survival.

RESULTS

There was no difference in length of stay (9 vs 8; p = 0.83), readmissions (27.6% vs 10.0%; p = 0.10), surgical re-interventions (15.0% vs 3.4%; p = 0.16), or stoma-free rate (52.6% vs 31.0%; p = 0.09) between immediate and delayed surgery groups. Hospital costs were similar in the delayed group (€11,913 vs €13,769; p = 0.89). Two-year overall survival (93% vs 100%; p = 0.23) and disease-free survival (78% vs 81%; p = 0.47) rates were comparable.

LIMITATIONS

Limitations included small sample size, follow-up time and retrospective design.

CONCLUSION

Delayed surgery for regrowth in a watch-and-wait program or for persistent residual disease after a repeated assessment is not associated with an increased risk of postoperative morbidity or a significant rise in costs compared to immediate total mesorectal excision. There also appears to be no evident compromise in oncological outcome. Repeated response assessment in patients with a near complete clinical response after neoadjuvant chemoradiotherapy is a useful approach to identify more patients who can benefit from a watch-and-wait strategy. See Video Abstract at http://links.lww.com/DCR/B836 .

CIRUGA DE TME RETRASADA EN UNA ESTRATEGIA DE WATCH AND WAIT DESPUS DE LA QUIMIORRADIOTERAPIA NEOADYUVANTE PARA CNCER DE RECTO UN ANLISIS DE COSTOS HOSPITALARIOS, Y DE RESULTADOS QUIRRGICOS Y ONCOLGICOS

ANTECEDENTES: Una estrategia de Watch and Wait para pacientes con cáncer de recto con una respuesta clínica completa después de quimiorradioterapia neoadyuvante es una alternativa valiosa en vez de resección rectal. Sin embargo, hay pacientes que tendrán tumor residual o un recrecimiento durante el Watch and Wait .OBJETIVO: El objetivo fue investigar la seguridad y los costos para los pacientes que se sometieron a una cirugía diferida después de la quimiorradioterapia neoadyuvante.DISEÑO: Este es un estudio de cohorte retrospectivo con datos recolectados prospectivamente.AJUSTE: El estudio se llevó a cabo en un gran hospital universitario.PACIENTES: Entre enero de 2015 y mayo de 2020, se atendieron 622 nuevos pacientes con cáncer de recto, de los cuales 200 recibieron quimiorradioterapia neoadyuvante. Se incluyeron 94 pacientes, de los cuales 65 se sometieron a cirugía inmediata y 29 pacientes requirieron cirugía diferida después de un enfoque inicial de observación y espera.PRINCIPALES MEDIDAS DE RESULTADO: se incluyeron la tasa de morbilidad posoperatoria a 30 días, los costos hospitalarios y las sobrevidas general y libre de enfermedad a dos años.RESULTADOS: No hubo diferencia en la duración de la estancia (9 vs 8, p = 0,83), reingresos (27,6% vs 10,0%, p = 0,10), reintervenciones quirúrgicas (15,0% vs 3,4%, p = 0,16) y tasa libre de estoma (52,6% vs 31,0%, p = 0,09) entre los grupos de cirugía inmediata y tardía. Los costos hospitalarios fueron similares en el grupo retrasado (11913 € frente a 13769 €, p = 0,89). Las tasas de sobrevida general a dos años (93% frente a 100%, p = 0,23) y sobrevida libre de enfermedad (78% frente a 81%, p = 0,47) fueron comparables.LIMITACIONES: Tamaño de muestra pequeño, tiempo de seguimiento y diseño retrospectivo.CONCLUSIÓN: La cirugía tardía para el recrecimiento en un programa de Watch and Wait o para la enfermedad residual persistente después de una evaluación repetida no se asocia con un riesgo mayor de morbilidad posoperatoria ni con un aumento significativo en los costos, en comparación con la escisión total de mesorrecto inmediata. Tampoco parece haber un compromiso evidente en el resultado oncológico. La evaluación repetida de la respuesta en pacientes con una respuesta clínica casi completa después de la quimiorradioterapia neoadyuvante es un enfoque útil para identificar más pacientes que pueden beneficiarse de una estrategia de Watch and Wait . Consulte Video Resumen en http://links.lww.com/DCR/B836 . (Traducción-Dr. Juan Carlos Reyes ).

Predictive biomarkers in radioresistant rectal cancer: a systematic review

BACKGROUND AND AIMS

The treatment of locally advanced rectal cancer often consists of neoadjuvant chemoradiotherapy followed by surgery. However, approximately 15% of patients show no response to this neoadjuvant chemoradiotherapy. This systematic review aimed to identify biomarkers of innate radioresistant rectal cancer.

METHOD

Through a systematic literature search, 125 papers were included and analyzed using ROBINS-I, a Cochrane risk of bias tool for non-randomized studies of interventions. Both statistically significant and nonsignificant biomarkers were identified. Biomarkers mentioned more than once in the results or biomarkers with a low or moderate risk of bias were included as the final results.

RESULTS

Thirteen unique biomarkers, three genetic signatures, one specific pathway, and two combinations of two or four biomarkers were identified. In particular, the connection between HMGCS2, COASY, and PI3K-pathway seems promising. Future scientific research should focus on further validating these genetic resistance markers.

Circulating Biomarkers in Predicting Pathological Response to Neoadjuvant Therapy for Colorectal Cancer

Circulating biomarkers show promise in the management of many cancers. They have become the novel non-invasive approach to complement the current strategies in colorectal cancer (CRC) management. Their ability in guiding diagnosis, evaluating response to treatment, screening and prognosis is phenomenal, especially when it comes to their minimally invasive nature. These “liquid biopsies,” which show potential for replacing invasive surgical biopsies, provide useful information on the primary and metastatic disease by providing an insight into cancer biology. Analysis of blood and body fluids for circulating tumour DNA (ctDNA), carcinoembryonic antigen (CEA), circulating tumour cells (CTC), or circulating micro RNA (miRNA) shows potential for improving CRC management. Recognizing a predictive model to assess response to neoadjuvant chemotherapy would help in better patient selection. This review was conducted with the aim of outlining the use of circulatory biomarkers in current practice and their effectiveness in the management of patients having CRC with a focus on response to neoadjuvant therapy.

Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models

Radiomics analyses commonly apply imaging features of different complexity for the prediction of the endpoint of interest. However, the prognostic value of each feature class is generally unclear. Furthermore, many radiomics models lack independent external validation that is decisive for their clinical application. Therefore, in this manuscript we present two complementary studies. In our modelling study, we developed and validated different radiomics signatures for outcome prediction after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) based on computed tomography (CT) and T2-weighted (T2w) magnetic resonance (MR) imaging datasets of 4 independent institutions (training: 122, validation 68 patients). We compared different feature classes extracted from the gross tumour volume for the prognosis of tumour response and freedom from distant metastases (FFDM): morphological and first order (MFO) features, second order texture (SOT) features, and Laplacian of Gaussian (LoG) transformed intensity features. Analyses were performed for CT and MRI separately and combined. Model performance was assessed by the area under the curve (AUC) and the concordance index (CI) for tumour response and FFDM, respectively. Overall, intensity features of LoG transformed CT and MR imaging combined with clinical T stage (cT) showed the best performance for tumour response prediction, while SOT features showed good performance for FFDM in independent validation (AUC = 0.70, CI = 0.69). In our external validation study, we aimed to validate previously published radiomics signatures on our multicentre cohort. We identified relevant publications on comparable patient datasets through a literature search and applied the reported radiomics models to our dataset. Only one of the identified studies could be validated, indicating an overall lack of reproducibility and the need of further standardization of radiomics before clinical application.

Biomarkers of Favorable vs. Unfavorable Responses in Locally Advanced Rectal Cancer Patients Receiving Neoadjuvant Concurrent Chemoradiotherapy

Colorectal cancer is the second leading cause of cancer death globally. The gold standard for locally advanced rectal cancer (LARC) nowadays is preoperative concurrent chemoradiation (CCRT). Approximately three quarters of LARC patients do not achieve pathological complete response and hence suffer from relapse, metastases and inevitable death. The exploration of trustworthy and timely biomarkers for CCRT response is urgently called for. This review focused upon a broad spectrum of biomarkers, including circulating tumor cells, DNA, RNA, oncogenes, tumor suppressor genes, epigenetics, impaired DNA mismatch repair, patient-derived xenografts, in vitro tumor organoids, immunity and microbiomes. Utilizing proper biomarkers can assist in categorizing appropriate patients by the most efficient treatment modality with the best outcome and accompanied by minimal side effects. The purpose of this review is to inspect and analyze accessible data in order to fully realize the promise of precision oncology for rectal cancer patients.

SLC35E2 promoter mutation as a prognostic marker of esophageal squamous cell carcinoma

AIMS

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest digestive tract cancer with poor prognosis. In our previous comprehensive genomics study, we identified that hotspot mutations in the solute carrier family 35 member E2 (SLC35E2) promoter region was significantly associated with worse prognosis in patients with ESCC. However, the biological function and molecular mechanism of SLC35E2 remains unclear. This study was to investigate the malignant function and mechanism of SLC35E2 in ESCC.

MAIN METHODS

Western blotting and qRT-PCR were used to assess the expression of SLC35E2 in ESCC cell lines. Luciferase assay and chromatin immunoprecipitation (ChIP) assay were used to assess the transcriptional inhibition of KLF4. Incucyte cell proliferation assay, colony formation assay and subcutaneous tumor formation in nude mice were used to assess the malignant function of SLC35E2.

KEY FINDINGS

SLC35E2 can promote ESCC cell proliferation in vitro and in vivo. Krüppel-like factor 4 (KLF4), a transcriptional repressor in ESCC, binds to the SLC35E2 promoter and represses the expression of SLC35E2. The transcriptional suppression of KLF4 can be blocked by the mutation at -118 site of the SLC35E2 promoter. Besides, the accumulation of SLC35E2 expression contributes to the malignant phenotype of ESCC.

SIGNIFICANCE

These results indicate that SLC35E2 may be used as a biomarker for prognosis as well as a therapeutic target for patients with ESCC.

The "Immunoscore" in rectal cancer: could we search quality beyond quantity of life?

Because of the function and anatomical environment of the rectum, therapeutic strategies for local advanced rectal cancer (LARC) must deal with two challenging stressors that are a high-risk of local and distal recurrences and a high-risk of poor quality of life (QoL). Over the last three decades, advances in screening tests, therapies, and combined-modality treatment options and strategies have improved the prognosis of patients with LARC. However, owing to the heterogeneous nature of LARC and genetic status, the patient may not respond to a specific therapy and may be at increased risk of side-effects without the life-prolonging benefit. Indeed, each therapy can cause its own side-effects, which may worsen by a combination of treatments resulting in long-term poor QoL. In LARC, QoL has become even more essential with the increasing incidence of rectal cancer in young individuals. Herein, we analyzed the value of the Immunoscore-Biopsy (performed on tumor biopsy at diagnosis) in predicting outcomes, alone or in association with clinical and imaging data, for each therapy used in LARC.

Validation of Gene Expression-Based Predictive Biomarkers for Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

BACKGROUND

Neoadjuvant chemoradiotherapy (nCRT) followed by surgery is widely used for patients with locally advanced rectal cancer. However, response to nCRT varies substantially among patients, highlighting the need for predictive biomarkers that can distinguish non-responsive from responsive patients before nCRT. This study aimed to build novel multi-gene assays for predicting nCRT response, and to validate our signature and previously-reported signatures in multiple independent cohorts.

METHODS

Three microarray datasets of pre-therapeutic biopsies containing a total of 61 non-responders and 53 responders were used as the discovery cohorts to screen for genes that were consistently associated with nCRT response. The predictive values of signatures were tested in a meta-analysis using six independent datasets as the validation cohorts, consisted of a total of 176 non-responders and 99 responders.

RESULTS

We identified four genes, including BRCA1, GPR110, TNIK, and WDR4 in the discovery cohorts. Although our 4-gene signature and nine published signatures were evaluated, they were unable to predict nCRT response in the validation cohorts.

CONCLUSIONS

Although this is one of the largest studies addressing the validity of gene expression-based classifiers using pre-treatment biopsies from patients with rectal cancer, our findings do not support their clinically meaningful values to be predictive of nCRT response.

Biomarkers and cell-based models to predict the outcome of neoadjuvant therapy for rectal cancer patients

Rectal cancer constitutes approximately one-third of all colorectal cancers and contributes to considerable mortality globally. In contrast to colon cancer, the standard treatment for localized rectal cancer often involves neoadjuvant chemoradiotherapy. Tumour response rates to treatment show substantial inter-patient heterogeneity, indicating a need for treatment stratification. Consequently researchers have attempted to establish new means for predicting tumour response in order to assist in treatment decisions. In this review we have summarized published findings regarding potential biomarkers to predict neoadjuvant treatment response for rectal cancer tumours. In addition, we describe cell-based models that can be utilized both for treatment prediction and for studying the complex mechanisms involved.

A Genotype Signature for Predicting Pathologic Complete Response in Locally Advanced Rectal Cancer

PURPOSE

To construct and validate a predicting genotype signature for pathologic complete response (pCR) in locally advanced rectal cancer (PGS-LARC) after neoadjuvant chemoradiation.

METHODS AND MATERIALS

Whole exome sequencing was performed in 15 LARC tissues. Mutation sites were selected according to the whole exome sequencing data and literature. Target sequencing was performed in a training cohort (n = 202) to build the PGS-LARC model using regression analysis, and internal (n = 76) and external validation cohorts (n = 69) were used for validating the results. Predictive performance of the PGS-LARC model was compared with clinical factors and between subgroups. The PGS-LARC model comprised 15 genes.

RESULTS

The area under the curve (AUC) of the PGS model in the training, internal, and external validation cohorts was 0.776 (0.697-0.849), 0.760 (0.644-0.867), and 0.812 (0.690-0.915), respectively, and demonstrated higher AUC, accuracy, sensitivity, and specificity than cT stage, cN stage, carcinoembryonic antigen level, and CA19-9 level for pCR prediction. The predictive performance of the model was superior to clinical factors in all subgroups. For patients with clinical complete response (cCR), the positive prediction value was 94.7%.

CONCLUSIONS

The PGS-LARC is a reliable predictive tool for pCR in patients with LARC and might be helpful to enable nonoperative management strategy in those patients who refuse surgery. It has the potential to guide treatment decisions for patients with different probability of tumor regression after neoadjuvant therapy, especially when combining cCR criteria and PGS-LARC.

Time interval between neoadjuvant radio-chemotherapy and surgery in rectal cancer: is the long interval correct for all patients?

BACKGROUND

Optimal time between neoadjuvant radio-chemotherapy period and surgery remains controversial in patients with rectal cancer: an increasing number of studies show results in favour of a long interval.

METHODS

We conducted a retrospective analysis of the cases of low-middle rectal adenocarcinoma undergoing neoadjuvant RT-CT and surgery: the primary endpoint was the complete pathological response rate and the secondary endpoint the rate of complications. We analysed cases from 1/01/2003 to 31/12/2018 divided in two periods: from 2003 to 2010 (23 pts) and from 2011 to 2018 (23 pts). The two periods were characterised by two different surgical teams which use different time intervals (≤vs>8 weeks).

RESULTS

The pCR rate is 21.7% in both groups; as regards the complications, the difference between the two groups is in grade IIIb: 8.7% in the first group and 17.4% in the second group (p 0.66).

CONCLUSIONS

Although our study is based on a small number of patients, it shows the same rate of pCR with respect to two different time intervals; this suggests the need for studies based on the division of patients into subgroups and the evaluation of different time intervals in order to reach the best oncological outcomes.

Predicting pathological response to chemoradiotherapy for rectal cancer: a systematic review

Introduction: Pathological complete response (pCR) rates of approximately 20% following neoadjuvant long-course chemoradiotherapy for rectal cancer have given rise to non-operative or watch-and-wait (W&W) management. To improve outcomes there has been significant research into predictors of response. The goal is to optimize selection for W&W, avoid chemoradiotherapy in those who won't benefit and improve treatment to maximize the clinical complete response (cCR) rate and the number of patients who can be considered for W&W.Areas covered: A systematic review of articles published 2008-2018 and indexed in PubMed, Embase or Medline was performed to identify predictors of pathological response (including pCR and recognized tumor regression grades) to fluoropyrimidine-based chemoradiotherapy in patients who underwent total mesorectal excision for rectal cancer. Evidence for clinical, biomarker and radiological predictors is discussed as well as potential future directions.Expert opinion: Our current ability to predict the response to chemoradiotherapy for rectal cancer is very limited. cCR of 40% has been achieved with total neoadjuvant therapy. If neoadjuvant treatment for rectal cancer continues to improve it is possible that the treatment for rectal cancer may eventually parallel that of anal squamous cell carcinoma, with surgery reserved for the minority of patients who don't respond to chemoradiotherapy.

Identification of a Signature Comprising 5 Soluble Carrier Family Genes to Predict the Recurrence of Papillary Thyroid Carcinoma

RNA-sequencing data and relevant clinical data in The Cancer Genome Atlas for 502 samples of papillary thyroid cancer (PTC) were analyzed to determine the prognostic value of soluble carrier family genes in PTC. We analyzed soluble carrier family gene expression and function in the samples. Clustering identified 2 clusters in the data. Risk characteristics were identified using LASSO and Univariate Cox regression analysis, which divided the patients into low and high-risk groups. The expression levels of 88 soluble carrier genes were significantly different between tumors and normal tissue. The 2 PTC clusters had different clinical outcomes and distributions of gene expression. The expression levels of SFXN1, SLC12A4, SLC35A1, SLC35E1, and SLCO1C1 were markedly different between the 2 groups. The high risk and low risk groups had significant different prognoses (P < 0.05). Significant differences were identified for disease free survival (DFS), sex and T stage between the 2 subgroups. The risk score was identified as an independent prognostic variable (P < 0.05) and as a predictor of clinicopathological variables. In patients with PTC, solute carrier gene expression showed differential associations with clinicopathological variables. The 5 genes could be used as prognostic factors for PTC, particularly to predict PTC recurrence.

ceRNA Networks: The Backbone Role in Neoadjuvant Chemoradiotherapy Resistance/Sensitivity of Locally Advanced Rectal Cancer

Approximately 40% of rectal cancers during initial diagnosis are identified as locally advanced rectal cancers (LARCs), for which the standardized treatment scenario is total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT). nCRT can lead to discernible reductions in local relapse rate and distant metastasis rate in LARC patients, in whom previously inoperable tumors may potentially be surgically removed. However, only 4% to 20% cases can attain pathological complete response, and the remaining patients who are unresponsive to nCRT have to suffer from the side effects plus toxicities and may encounter poor survival outcomes due to the late surgical intervention. As such, employing potential biomarkers to differentiate responders from nonresponders before nCRT implementation appears to be the overarching goal. Well-defined competing endogenous RNA (ceRNA) networks include long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA and circRNA-miRNA-mRNA networks. As ceRNAs, lncRNAs, and circRNAs sponge miRNAs to indirectly suppress miRNAs downstream of oncogenic mRNAs or tumor-suppressive mRNAs. The abnormal expression of mRNAs regulates the nCRT-induced DNA damage repair process through pluralistic carcinogenic signaling pathways, thereby bringing about alterations in the nCRT resistance/sensitivity of tumors. Moreover, many molecular mechanisms relevant to cell proliferation, metastasis, or apoptosis of cancers (eg, epithelial-mesenchymal transition and caspase-9-caspase-3 pathway) are influenced by ceRNA networks. Herein, we reviewed a large group of abnormally expressed mRNAs and noncoding RNAs that are associated with nCRT resistance/sensitivity in LARC patients and ultimately pinpointed the backbone role of ceRNA networks in the molecular mechanisms of nCRT resistance/sensitivity.

Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study

Background

The aim of this work is to combine radiological and pathological information of tumor to develop a signature for pretreatment prediction of discrepancies of pathological response at several centers and restage patients with locally advanced rectal cancer (LARC) for individualized treatment planning.

Patients and Methods

A total of 981 consecutive patients with evaluation of response according to tumor regression grade (TRG) who received nCRT were retrospectively recruited from four hospitals (primary cohort and external validation cohort 1–3); both pretreatment multiparametric MRI (mp-MRI) and whole slide image (WSI) of biopsy specimens were available for each patient. Quantitative image features were extracted from mp-MRI and WSI and used to construct a radiopathomics signature (RPS) powered by an artificial-intelligence model. Models based on mp-MRI or WSI alone were also constructed for comparison.

Results

The RPS showed overall accuracy of 79.66–87.66% in validation cohorts. The areas under the curve of RPS at specific response grades were 0.98 (TRG0), 0.93 (≤ TRG1), and 0.84 (≤ TRG2). RPS at each grade of pathological response revealed significant improvement compared with both signatures constructed without combining multiscale tumor information (P < 0.01). Moreover, RPS showed relevance to distinct probabilities of overall survival and disease-free survival in patients with LARC who underwent nCRT (P < 0.05).

Conclusions

The results of this study suggest that radiopathomics, combining both radiological information of the whole tumor and pathological information of local lesions from biopsy, could potentially predict discrepancies of pathological response prior to nCRT for better treatment planning.

Electronic supplementary material

The online version of this article (10.1245/s10434-020-08659-4) contains supplementary material, which is available to authorized users.

Predicting Response to Neoadjuvant Therapy in Colorectal Cancer Patients the Role of Messenger-and Micro-RNA Profiling

Colorectal cancer patients' responses to neoadjuvant therapy undergo broad inter-individual variations. The aim of this systematic review is to identify a molecular signature that is predictive of colon cancer downstaging and/or downgrading after neoadjuvant therapy. Among the hundreds analysed in the available studies, only 19 messenger-RNAs (mRNAs) and six micro-RNAs (miRNAs) were differentially expressed in responders versus non-responders in two or more independent studies. Therefore, a mRNA/miRNA signature can be designed accordingly, with limitations caused by the retrospective nature of these studies, the heterogeneity in study designs and the downgrading/downstaging assessment criteria. This signature can be proposed to tailor neoadjuvant therapy regimens on an individual basis.

A Method to Extract Feature Variables Contributed in Nonlinear Machine Learning Prediction

BACKGROUND

Although advances in prediction accuracy have been made with new machine learning methods, such as support vector machines and deep neural networks, these methods make nonlinear machine learning models and thus lack the ability to explain the basis of their predictions. Improving their explanatory capabilities would increase the reliability of their predictions.

OBJECTIVE

Our objective was to develop a factor analysis technique that enables the presentation of the feature variables used in making predictions, even in nonlinear machine learning models.

METHODS

A factor analysis technique was consisted of two techniques: backward analysis technique and factor extraction technique. We developed a factor extraction technique extracted feature variables that was obtained from the posterior probability distribution of a machine learning model which was calculated by backward analysis technique.

RESULTS

In evaluation, using gene expression data from prostate tumor patients and healthy subjects, the prediction accuracy of a model of deep neural networks was approximately 5% better than that of a model of support vector machines. Then the rate of concordance between the feature variables extracted in an earlier report using Jensen-Shannon divergence and the ones extracted in this report using backward elimination using Hilbert-Schmidt independence criteria was 40% for the top five variables, 40% for the top 10, and 49% for the top 100.

CONCLUSION

The results showed that models can be evaluated from different viewpoints by using different factor extraction techniques. In the future, we hope to use this technique to verify the characteristics of features extracted by factor extraction technique, and to perform clinical studies using the genes, we extracted in this experiment.

Integrative Molecular Characterization of Resistance to Neoadjuvant Chemoradiation in Rectal Cancer

PURPOSE

Molecular properties associated with complete response or acquired resistance to concurrent chemotherapy and radiotherapy (CRT) are incompletely characterized.Experimental Design: We performed integrated whole-exome/transcriptome sequencing and immune infiltrate analysis on rectal adenocarcinoma tumors prior to neoadjuvant CRT (pre-CRT) and at time of resection (post-CRT) in 17 patients [8 complete/partial responders, 9 nonresponders (NR)].

RESULTS

CRT was not associated with increased tumor mutational burden or neoantigen load and did not alter the distribution of established somatic tumor mutations in rectal cancer. Concurrent KRAS/TP53 mutations (KP) associated with NR tumors and were enriched for an epithelial-mesenchymal transition transcriptional program. Furthermore, NR was associated with reduced CD4/CD8 T-cell infiltrates and a post-CRT M2 macrophage phenotype. Absence of any local tumor recurrences, KP/NR status predicted worse progression-free survival, suggesting that local immune escape during or after CRT with specific genomic features contributes to distant progression.

CONCLUSIONS

Overall, while CRT did not impact genomic profiles, CRT impacted the tumor immune microenvironment, particularly in resistant cases.

A Multigene Model for Predicting Tumor Responsiveness After Preoperative Chemoradiotherapy for Rectal Cancer

PURPOSE

Although preoperative chemoradiotherapy (PCRT) is regarded as a standard treatment for locally advanced rectal cancer, there is no reliable biomarker for predicting responsiveness to PCRT. We aimed to develop a biomarker model for predicting response to PCRT.

METHODS AND MATERIALS

We included 184 patients who received PCRT followed by surgical resection and categorized them as good responders (complete or near-complete regression) or poor responders (all other patients). Candidate gene mRNAs were isolated from formalin-fixed paraffin-embedded tumor specimens and analyzed using the NanoString nCounter gene expression assay. Stepwise logistic regression analysis was used to select genes in discovery and training phases. A quantitative radio-responsiveness prediction model was developed and validated using internal cross-validation groups, and the model's predictive value was assessed based on the area under the receiver operating characteristic curve (AUC).

RESULTS

By comparing the gene expressions between good and poor responders, we created a multigene mRNA model using FZD9, HRAS, ITGA7, MECOM, MMP3, NKD1, PIK3CD, and PRKCB. This panel showed good ability to predict treatment response (AUC: 0.846 for the whole data set). Internal cross-validation was performed to evaluate the model's predictive stability among 3 cohorts, which provided AUC values of 0.808-0.909. The satisfactory diagnostic performance of the radio-response prediction index persisted regardless of other clinicopathologic features such as clinical T or N stage, interval between radiation and surgery, and pretreatment carcinoembryonic antigen levels (P = .001, 95% CI, 0.686-0.905).

CONCLUSIONS

We developed a multigene mRNA-based biomarker model that allows prediction of rectal cancer response to PCRT, which may help identify patients who will benefit most from PCRT.

Effect of Akt activation and experimental pharmacological inhibition on responses to neoadjuvant chemoradiotherapy in rectal cancer

BACKGROUND

Neoadjuvant chemoradiotherapy (CRT) is one of the preferred initial treatment strategies for locally advanced rectal cancer. Responses are variable, and most patients still require surgery. The aim of this study was to identify molecular mechanisms determining poor response to CRT.

METHODS

Global gene expression and pathway enrichment were assessed in pretreatment biopsies from patients with non-metastatic cT2-4 N0-2 rectal cancer within 7 cm of the anal verge. Downstream Akt activation was assessed in an independent set of pretreatment biopsies and in colorectal cancer cell lines using immunohistochemistry and western blot respectively. The radiosensitizing effects of the Akt inhibitor MK2206 were assessed using clonogenic assays and xenografts in immunodeficient mice.

RESULTS

A total of 350 differentially expressed genes were identified, of which 123 were upregulated and 199 downregulated in tumours from poor responders. Mitochondrial oxidative phosphorylation (P < 0·001) and phosphatidylinositol signalling pathways (P < 0·050) were identified as significantly enriched pathways among the set of differentially expressed genes. Deregulation of both pathways is known to result in Akt activation, and high immunoexpression of phosphorylated Akt S473 was observed among patients with a poor histological response (tumour regression grade 0-2) to CRT (75 per cent versus 48 per cent in those with a good or complete response; P = 0·016). Akt activation was also confirmed in the radioresistant cell line SW480, and a 50 per cent improvement in sensitivity to CRT was observed in vitro and in vivo when SW480 cells were exposed to the Akt inhibitor MK2206 in combination with radiation and 5-fluorouracil.

CONCLUSION

Akt activation is a key event in the response to CRT. Pharmacological inhibition of Akt activation may enhance the effects of CRT. Surgical relevance Organ preservation is an attractive alternative in rectal cancer management following neoadjuvant chemoradiotherapy (CRT) to avoid the morbidity of radical surgery. Molecular steps associated with tumour response to CRT may provide a useful tool for the identification of patients who are candidates for no immediate surgery. In this study, tumours resistant to CRT were more likely to have activation of specific genetic pathways that result in phosphorylated Akt (pAkt) activation. Pretreatment biopsy tissues with high immunoexpression of pAkt were more likely to exhibit a poor histological response to CRT. In addition, the introduction of a pAkt inhibitor to cancer cell lines in vitro and in vivo led to a significant improvement in sensitivity to CRT. Identification of pAkt-activated tumours may thus allow the identification of poor responders to CRT. In addition, the concomitant use of pAkt inhibitors to increase sensitivity to CRT in patients with rectal cancer may constitute an interesting strategy for increasing the chance of a complete response to treatment and organ preservation.

Non-operative management of rectal cancer: understanding tumor biology

The management of locally-advanced rectal cancer involves a combination of chemotherapy, chemoradiation, and surgical resection to provide excellent local tumor control and overall survival. However, aspects of this multimodality approach are associated with significant morbidity and long-term sequelae. In addition, there is growing evidence that patients with a clinical complete response to chemotherapy and chemoradiation treatments may be safely offered initial non-operative management in a rigorous surveillance program. Weighed against the morbidity and significant sequelae of rectal resection, recognizing how to best optimize non-operative strategies without compromising oncologic outcomes is critical to our understanding and treatment of this disease.

Clinical and molecular diagnosis of pathologic complete response in rectal cancer: an update

INTRODUCTION

The standard of care for locally advanced rectal cancer includes neoadjuvant chemoradiation with subsequent total mesorectal excision. This approach has shown various degrees of response to neoadjuvant chemoradiation (ranging from complete response to further tumor growth), which have substantial prognostic and therapeutic implications. A total regression of the tumor is a predictor of superior oncologic outcomes compared with partial responders and non-responders. Further, this concept has opened the possibility of nonoperative strategies for complete responders and explains the widespread research interest in finding clinical, radiographic, pathologic, and biochemical parameters that allow for identification of these patients. Areas covered: The present review evaluates the most recent efforts in the literature to identify predictors of patients likely to achieve a complete response following neoadjuvant treatment for the management of rectal cancer. This includes clinical predictors of pathologic complete response such as tumor location, size, and stage, molecular predictors such as tumor biology and microRNA, serum biomarkers such as carcinoembryogenic antigen and nomograms. Expert commentary: There has been significant progress in our ability to predict pathological complete response. However, more high-quality research is still needed to use this concept to confidently dictate clinical management.

The potential predictive value of DEK expression for neoadjuvant chemoradiotherapy response in locally advanced rectal cancer

BACKGROUND

Limited data are available regarding the ability of biomarkers to predict complete pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Complete response translates to better patient survival. DEK is a transcription factor involved not only in development and progression of different types of cancer, but is also associated with treatment response. This study aims to analyze the role of DEK in complete pathological response following chemoradiotherapy for locally advanced rectal cancer.

METHODS

Pre-treated tumour samples from 74 locally advanced rectal-cancer patients who received chemoradiation therapy prior to total mesorectal excision were recruited for construction of a tissue microarray. DEK immunoreactivity from all samples was quantified by immunohistochemistry. Then, association between positive stained tumour cells and pathologic response to neoadjuvant treatment was measured to determine optimal predictive power.

RESULTS

DEK expression was limited to tumour cells located in the rectum. Interestingly, high percentage of tumour cells with DEK positiveness was statistically associated with complete pathological response to neoadjuvant treatment based on radiotherapy and fluoropyrimidine-based chemotherapy and a marked trend toward significance between DEK positiveness and absence of treatment toxicity. Further analysis revealed an association between DEK and the pro-apoptotic factor P38 in the pre-treated rectal cancer biopsies.

CONCLUSIONS

These data suggest DEK as a potential biomarker of complete pathological response to treatment in locally advanced rectal cancer.

The toxin BjussuLAAO-II induces oxidative stress and DNA damage, upregulates the inflammatory cytokine genes TNF and IL6, and downregulates the apoptotic-related genes BAX, BCL2 and RELA in human Caco-2 cells

Colorectal carcinoma is one of the most common cancers in adults. As chemotherapy, the first-choice treatment for colorectal carcinoma, is often infeasible due to acquired tumor resistance and several adverse effects, it is important to discover and explore new molecules with better therapeutic action. Snake venom toxins have shown promising results with high cytotoxicity against tumor cells, but their mechanisms of action remain unclear. Here we examined how BjussuLAAO-II, an L-amino acid oxidase isolated from Bothrops jararacussu snake venom, exerts cytotoxicity towards colorectal adenocarcinoma human cells (Caco-2) and human umbilical vein endothelial cell line (HUVEC). A 24-h treatment with BjussuLAAO-II at 0.25 - 5.00 μg/mL diminished cell viability by decreasing (i) mitochondrial activity, assessed by reduction of 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide and resazurin; (ii) the activity of acid phosphatases; and (iii) lysosomal function, assessed by neutral red uptake. BjussuLAAO-II also increased intracellular levels of reactive oxygen species and DNA damage, as assessed by fluorescence and the comet assay, respectively. BjussuLAAO-II altered the expression of cell proliferation-related genes, as determined by RT-qPCR: it elevated the expression of the inflammatory cytokine genes TNF and IL6, and lowered the expression of the apoptotic-related genes BAX, BCL2, and RELA. Therefore, BjussuLAAO-II induces Caco-2 cells death by acting on multiple intracellular targets, providing important data for further studies to assess whether these effects are seen in both tumor and normal cells, with the aim of selecting this drug for possible therapeutic purposes in the future.

Management of the Complete Clinical Response

Organ preservation is considered in the management of selected patients with rectal cancer. Complete clinical response observed after neoadjuvant chemoradiation for rectal cancer is one of these cases. Patients who present complete clinical response are candidates to the watch-and-wait approach, when radical surgery is not immediately performed and is offered only to patients in the event of a local relapse. These patients are included in a strict follow-up, and up of 70% of them will never be operated during the follow-up. This strategy is associated with similar oncological outcomes as patients operated on, and the advantage of avoiding the morbidity associated to the radical operation. In this article we will discuss in detail the best candidates for this approach, the protocol itself, and the long-term outcomes.

Molecular Biology: Are We Getting Any Closer to Providing Clinically Useful Information?

Advances in molecular biology and biomarker research have significantly impacted our understanding and treatment of multiple solid malignancies. In rectal cancer, where neoadjuvant chemoradiation is widely used for locally advanced disease, most efforts have focused on the identification of predictors of response in an attempt to appropriately select patients for multimodality therapy. A variety of biomarkers have been studied, including genetic mutations, chromosomal copy number alterations, and single as well as multigene expression patterns. Also, as transanal resection of rectal tumors requires accurate preoperative detection of lymph node metastasis, the identification of biomarkers of regional nodal involvement has been another important field of active research. While preliminary results have been promising, lack of external validation means has a limited translation to clinical use. This review summarizes recent developments in rectal cancer biomarker research, highlighting the challenges associated with their adoption, and evaluating their potential for clinical use.

Intratumoral Genetic Heterogeneity in Rectal Cancer: Are Single Biopsies representative of the entirety of the tumor?

OBJECTIVE

Demonstrate intratumoral genetic heterogeneity in rectal cancer.

BACKGROUND

Several clinical management decisions in rectal cancer may be influenced by pretreatment biopsy information. However, in the setting of significant intratumoral heterogeneity, biopsies may not be representative of the entirety of the tumor and limit the reliability of the information provided from them for clinical decision management.

METHODS

Three fragments from a single rectal adenocarcinoma were chosen for whole-exome sequencing followed by mutation detection analysis. About 25 Gb of unambiguously mapped sequences were generated for each sample resulting in a median fold-coverage of 35x. Captured sequences mapped to the reference human genome were then used for the detection of somatic point mutations.

RESULTS

Overall, 193 unique somatic point mutations were identified. Only 53 (27%) of these were shared by all three fragments, including known genes involved in early phases of the adenoma-carcinoma sequence (such as, APC). Approximately, 115 (59%) mutations were exclusively present in only one of the fragments, including mutations in "driver" genes (DNAH12). Jaccard distances showed a median distance of 0.603 for pair-wise comparison of fragments indicating significant heterogeneity between them.

CONCLUSIONS

Considerable intratumoral heterogeneity is present among naive rectal cancers. The majority of point mutations detected in different fragments from rectal cancers are frequently unique to a single fragment. These findings support that gene mutations found on single pretreatment biopsies will not necessarily be representative of mutations present in the entirety of the tumor and therefore may limit the utility of the biological information provided by single biopsy fragments for clinical management decisions.

Gene signatures associated with drug resistance to irinotecan and oxaliplatin predict a poor prognosis in patients with colorectal cancer

The identification of novel survival predictors may help to improve the appropriate management of colorectal cancer (CRC). In the present study, two gene sets associated with irinotecan or oxaliplatin resistance in CRC cell lines were first identified and subsequently applied to the clinical CRC microarray dataset GSE14333. Subsequently, a 60-gene irinotecan resistance-associated signature and a 13-gene oxaliplatin resistance-associated signature were established, which were able to classify CRC patients into high- and low-risk subgroups with varied clinical outcomes [irinotecan-resistance gene signature: hazard ratio (HR)=0.4607, 95% confidence interval (CI)=0.3369-0.6300, P<0.0001; oxaliplatin-resistance gene signature: HR=0.6119, 95% CI=0.4547-0.8233, P=0.0008]. The performance of these two gene expression signatures in predicting outcome risk were also validated in two other independent CRC gene expression microarray datasets, GSE17536 (irinotecan-resistance gene signature: HR=0.5318, 95% CI=0.3359-0.8419, P=0.0079; oxaliplatin-resistance gene signature: HR=0.5383, 95% CI=0.3400-0.8521, P=0.0114) and GSE17537 (irinotecan-resistance gene signature: HR=0.2827, 95% CI=0.1173-0.6813, P=0.0088; oxaliplatin-resistance gene signature: HR=0.2378, 95% CI=0.09773-0.5784, P=0.0023). Furthermore, the combination of these two gene classifiers demonstrated a superior performance in CRC prognosis prediction than either used individually. Therefore, this study proposed novel gene classifier models for CRC prognosis prediction, which may be potentially useful to inform treatment decisions for patients with CRC in clinical settings.

Discriminating cancer-related and cancer-unrelated chemoradiation-response genes for locally advanced rectal cancers

For patients with locally advanced rectal cancer (LARC) treated with preoperation chemoradiation (pCRT), identifying differentially expressed (DE) genes between non-responders and responders is a common approach for investigating mechanisms of chemoradiation resistance. However, some of such DE genes might be irrelevant to cancer itself but simply reflect the pharmacokinetic differences of the normal tissues. In this study, we adopted the RankComp algorithm to identify DE genes for each of LARC sample compared with its own normal state. Then, we identified genes with significantly different deregulation frequencies between the non-responders and responders, defined as cancer-related pCRT-response genes. Pathway enrichment and protein-protein interaction analyses showed that these genes specifically and intensively interacted with currently known effective genes of pCRT, involving in DNA replication, cell cycle and DNA repair. In contrast, after excluding the cancer-related pCRT-response genes, the other DE genes between non-responders and responders were enriched in many pathways of drug and protein metabolisms and transports, and interacted with both the known effective genes and pharmacokinetic genes. Hence, these two types of DE genes should be distinguished for investigating mechanisms of pCRT response in LARCs.

Current debate in the oncologic management of rectal cancer

Despite the considerable amount of research in the field, the management of locally advanced rectal cancer remains a subject to debate. To date, effective treatment centers on surgical resection with the standard approach of total mesorectal resection. Radiation therapy and chemotherapy have been incorporated in order to decrease local and systemic recurrence. While it is accepted that a multimodality treatment regimen is indicated, there remains significant debate for how best to accomplish this in regards to order, dosing, and choice of agents. Preoperative radiation is the standard of care, yet remains debated with the option for chemoradiation, short course radiation, and even ongoing studies looking at the possibility of leaving radiation out altogether. Chemotherapy was traditionally incorporated in the adjuvant setting, but recent reports suggest the possibility of improved efficacy and tolerance when given upfront. In this review, the major studies in the management of locally advanced rectal cancer will be discussed. In addition, future directions will be considered such as the role of immunotherapy and ongoing trials looking at timing of chemotherapy, inclusion of radiation, and non-operative management.

Gene and MicroRNA Expression Are Predictive of Tumor Response in Rectal Adenocarcinoma Patients Treated With Preoperative Chemoradiotherapy

Preoperative chemoradiotherapy (pCRT) followed by surgery is the standard treatment for locally advanced rectal cancer (LARC). However, tumor response to pCRT is not uniform, and there are no effective predictive methods. This study investigated whether specific gene and miRNA expression are associated with tumor response to pCRT. Tissue biopsies were obtained from patients before pCRT and resection. Gene and miRNA expression were analyzed using a one-color microarray technique that compares signatures between responders (R) and non-responders (NR), as measured based on tumor regression grade. Two groups composed of 38 "exploration cohort" and 21 "validation cohort" LARC patients were considered for a total of 32 NR and 27 R patients. In the first cohort, using SAM Two Class analysis, 256 genes and 29 miRNAs that were differentially expressed between the NR and R patients were identified. The anti-correlation analysis showed that the same 8 miRNA interacted with different networks of transcripts. The miR-630 appeared only with the NR patients and was anti-correlated with a single transcript: RAB5B. After PAM, the following eight transcripts were strong predictors of tumor response: TMEM188, ITGA2, NRG, TRAM1, BCL2L13, MYO1B, KLF7, and GTSE1. Using this gene set, an unsupervised cluster analysis was applied to the validation cohort and correctly assigned the patients to the NR or R group with 85.7% accuracy, 90% sensitivity, and 82% specificity. All three parameters reached 100% when both cohorts were considered together. In conclusion, gene and miRNA expression profiles may be helpful for predicting response to pCRT in LARC patients. J. Cell. Physiol. 232: 426-435, 2017. © 2016 Wiley Periodicals, Inc.

SF3A1 and pancreatic cancer: new evidence for the association of the spliceosome and cancer

A two-stage case-control study was conducted to examine the association between six candidate U2-depedent spliceosome genes (SRSF1, SRSF2, SF3A1, SF3B1, SF1 and PRPF40B) and pancreatic cancer (PC). Subjects with one or two T alleles at rs2074733 in SF3A1 had a lower risk of PC compared to those with two C alleles in combined two populations (OR: 0.59, 95% confidence interval: 0.48–0.73, False discovery rate (FDR)-P = 1.5E-05). Moreover, the presence of the higher-risk genotype at rs2074733 plus smoking or drinking had synergic effects on PC risk. These findings illustrate that RNA splicing-related genes appear to be associated with the occurrence of PC, and show synergic interactions with smoking and drinking in the additive model. In the future, our novel findings should be further confirmed by functional studies and independent large-scale population studies.

An integrative approach for the identification of prognostic and predictive biomarkers in rectal cancer

Introduction

Colorectal cancer is the third most common cancer in the world, a small fraction of which is represented by locally advanced rectal cancer (LARC). If not medically contraindicated, preoperative chemoradiotherapy, represent the standard of care for LARC patients. Unfortunately, patients shows a wide range of response rates in which approximately 20% has a complete pathological response, whereas in 20 to 40% the response is poor or absent.

Results

The following specific gene signature, able to discriminate responders' patients from non-responders, were founded: AKR1C3, CXCL11, CXCL10, IDO1, CXCL9, MMP12 and HLA-DRA. These genes are mainly involved in immune system pathways and interact with drugs traditionally used in the adjuvant treatment of rectal cancer.

Discussion

The present study suggests that new ideas for therapy could be found not only limited to studying genes differentially expressed between the two groups of patients but deepening the mechanisms, associated to response, in which they are involved.

Methods

Gene expression studies performed by: Agostini et al., Rimkus et al. and Kim et al. have been merged through a meta-analysis of the raw data. Gene expression data-sets have been processed using A-MADMAN. Common differentially expressed gene (DEG) were identified through SAM analysis. To further characterize the identified DEG we deeply investigated its biological role using an integrative computational biology approach.

Predicting multi-class responses to preoperative chemoradiotherapy in rectal cancer patients

Background

Preoperative chemoradiotherapy (CRT) has become a widely used treatment for improving local control of disease and increasing survival rates of rectal cancer patients. We aimed to identify a set of genes that can be used to predict responses to CRT in patients with rectal cancer.

Methods

Gene expression profiles of pre-therapeutic biopsy specimens obtained from 77 rectal cancer patients were analyzed using DNA microarrays. The response to CRT was determined using the Dworak tumor regression grade: grade 1 (minimal, MI), grade 2 (moderate, MO), grade 3 (near total, NT), or grade 4 (total, TO).

Results

Top ranked genes for three different feature scores such as a p-value (pval), a rank product (rank), and a normalized product (norm) were selected to distinguish pre-defined groups such as complete responders (TO) from the MI, MO, and NT groups. Among five different classification algorithms, supporting vector machine (SVM) with the top 65 norm features performed at the highest accuracy for predicting MI using a 5-fold cross validation strategy. On the other hand, 98 pval features were selected for predicting TO by elastic net (EN). Finally we combined TO- and MI-finder models to build a three-class classification model and validated it using an independent dataset of rectal cancer mRNA expression.

Conclusions

We identified MI- and TO-finders for predicting preoperative CRT responses, and validated these data using an independent public dataset. This stepwise prediction model requires further evaluation in clinical studies in order to develop personalized preoperative CRT in patients with rectal cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-016-0623-9) contains supplementary material, which is available to authorized users.

Predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review

AIM

Approximately 20% of patients treated with neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer achieve a pathological complete response (pCR) while the remainder derive the benefit of improved local control and downstaging and a small proportion show a minimal response. The ability to predict which patients will benefit would allow for improved patient stratification directing therapy to those who are likely to achieve a good response, thereby avoiding ineffective treatment in those unlikely to benefit.

METHOD

A systematic review of the English language literature was conducted to identify pathological factors, imaging modalities and molecular factors that predict pCR following chemoradiotherapy. PubMed, MEDLINE and Cochrane Database searches were conducted with the following keywords and MeSH search terms: 'rectal neoplasm', 'response', 'neoadjuvant', 'preoperative chemoradiation', 'tumor response'. After review of title and abstracts, 85 articles addressing the prediction of pCR were selected.

RESULTS

Clear methods to predict pCR before chemoradiotherapy have not been defined. Clinical and radiological features of the primary cancer have limited ability to predict response. Molecular profiling holds the greatest potential to predict pCR but adoption of this technology will require greater concordance between cohorts for the biomarkers currently under investigation.

CONCLUSION

At present no robust markers of the prediction of pCR have been identified and the topic remains an area for future research. This review critically evaluates existing literature providing an overview of the methods currently available to predict pCR to nCRT for locally advanced rectal cancer. The review also provides a comprehensive comparison of the accuracy of each modality.

New Perspectives on Predictive Biomarkers of Tumor Response and Their Clinical Application in Preoperative Chemoradiation Therapy for Rectal Cancer

Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10-30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment.

Prediction of response to preoperative chemoradiotherapy and establishment of individualized therapy in advanced rectal cancer

Preoperative chemoradiotherapy (CRT) has become the standard treatment for patients with locally advanced rectal cancer. However, no specific biomarker has been identified to predict a response to preoperative CRT. The aim of the present study was to assess the gene expression patterns of patients with advanced rectal cancer to predict their responses to preoperative CRT. Fifty-nine rectal cancer patients were subjected to preoperative CRT. Patients were randomly assigned to receive CRT with tegafur/gimeracil/oteracil (S-1 group, n=30) or tegafur-uracil (UFT group, n=29). Gene expression changes were studied with cDNA and miRNA microarray. The association between gene expression and response to CRT was evaluated. cDNA microarray showed that 184 genes were significantly differentially expressed between the responders and the non‑responders in the S-1 group. Comparatively, 193 genes were significantly differentially expressed in the responders in the UFT group. TBX18 upregulation was common to both groups whereas BTNL8, LOC375010, ADH1B, HRASLS2, LOC284232, GCNT3 and ALDH1A2 were significantly differentially lower in both groups when compared with the non-responders. Using miRNA microarray, we found that 7 and 16 genes were significantly differentially expressed between the responders and non-responders in the S-1 and UFT groups, respectively. miR-223 was significantly higher in the responders in the S-1 group and tended to be higher in the responders in the UFT group. The present study identified several genes likely to be useful for establishing individualized therapies for patients with rectal cancer.

A Bagged, Partially Linear, Tree-Based Regression Procedure for Prediction and Variable Selection

OBJECTIVES

In genomics, variable selection and prediction accounting for the complex interrelationships between explanatory variables represent major challenges. Tree-based methods are powerful alternatives to classical regression models. We have recently proposed the generalized, partially linear, tree-based regression (GPLTR) procedure that integrates the advantages of generalized linear regression (allowing the incorporation of confounding variables) and of tree-based models. In this work, we use bagging to address a classical concern of tree-based methods: their instability.

METHODS

We present a bagged GPLTR procedure and three scores for variable importance. The prediction accuracy and the performance of the scores are assessed by simulation. The use of this procedure is exemplified by the analysis of a lung cancer data set. The aim is to predict the epidermal growth factor receptor (EGFR) mutation based on gene expression measurements, taking into account the ethnicity (confounder variable) and perform variable selection.

RESULTS

The procedure performs well in terms of prediction accuracy. The scores differentiate predictive variables from noise variables. Based on a lung adenocarcinoma data set, the procedure achieves good predictive performance for EGFR mutation and selects relevant genes.

CONCLUSION

The proposed bagged GPLTR procedure performs well for prediction and variable selection.

MicroRNA-21 predicts response to preoperative chemoradiotherapy in locally advanced rectal cancer

PURPOSE

The treatment of choice for locally advanced rectal cancer is preoperative chemoradiotherapy. Despite half of patients do not respond and suffer unnecessary toxicities and surgery delays, there are no biomarkers to guide preoperative CRT outcome. MicroRNA-21 has been related to acquisition of 5-fluorouracil resistance; however, its potential predictive value of response to preoperative chemoradiotherapy in locally advanced rectal cancer remains unknown.

METHODS

Nighty-two patients diagnosed with locally advanced rectal cancer who were preoperatively treated with chemoradiotherapy were selected for this study. Moreover, microRNA-21 expression was quantified in formalin-fixed paraffin-embedded biopsies from this cohort, and the results obtained were correlated with clinical and molecular characteristics, pathological response, and outcome.

RESULTS

MicroRNA-21 was found overexpressed in 77.6% cases, and significantly correlated with tumor grade after preoperative chemoradiotherapy (P = 0.013) and with pathological response (P = 0.013). The odds ratio of having miR-21 overexpression and not getting a respond to chemoradiotherapy resulted in 9.75 CI 2.24 to 42. Sensitivity, specificity, negative predictive values, and positive predictive value were 86.6, 60, 42.8, and 92%, respectively. Multivariate analysis confirmed the clinical significance of miR-21 determining preoperative chemoradiotherapy response.

CONCLUSIONS

MicroRNA-21 expression efficiently predicts preoperative chemoradiotherapy pathological response in locally advanced rectal cancer.