Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

A deep neural network predictor to predict the sensitivity of neoadjuvant chemoradiotherapy in locally advanced rectal cancer

Neoadjuvant chemoradiotherapy (NCRT) is widely used for locally advanced rectal cancer (LARC). This study aimed to conduct an effective model to predict NCRT sensitivity and provide guidance for clinical treatment. Biomarkers for NCRT sensitivity were identified by applying transcriptome profiles using logistic regression and subsequently screened out by Spearman correlation analysis and four machine learning algorithms. A deep neural network (DNN) predictor was constructed by using in-house dataset and validated in two independent datasets. Additionally, a web-based program was developed. Wnt/β-catenin signaling and linoleic acid metabolism (LA) pathways were associated with NCRT sensitivity and prognosis in LARC, antagonistically. A DNN predictor with an 18-gene signature was conducted within in-house datasets. In two validation cohorts, area under ROC curve (AUC) achieved 0.706 and 0.897. The DNN subtypes were significantly associated with NCRT sensitivity, survival status et al. Moreover, NK and cytotoxic T cells were observed contribution to NCRT sensitivity while regulatory T, myeloid-derived suppressor cells and dysfunction of CD4 T effector memory cells could impede NCRT response. A DNN predictor could predict NCRT sensitivity in LARC and stratify LARC patients with different clinical and immunity characteristic.

Lipid metabolism-associated genes serve as potential predictive biomarkers in neoadjuvant chemoradiotherapy combined with immunotherapy in rectal cancer

BACKGROUND

The aim of this study was to investigate the potential role of lipid metabolism-associated genes (LMAGs) in neoadjuvant chemoradiotherapy (nCRT) and immunotherapy for rectal cancer.

METHODS

Differential LMAGs were characterized and functional enrichment analysis was performed. Multiple machine learning algorithms were combined to explore candidate LMAGs. ROC analysis was performed to evaluate the predicting accuracy of candidate LMAGs. The expression patterns, prognostic value, genetic alterations, and immune cell infiltration of the top-ranked LMAGs were investigated.

RESULTS

We identified 45 LMAGs that were differentially expressed in tumor samples of nCRT responders and non-responders. These LMAGs were closely associated with lipid metabolism-related biological processes and pathways. ROC analysis revealed that the SREBF2 gene, an important transcription factor in regulating lipid metabolism, was the highest predictor of nCRT in rectal cancer. SREBF2 was highly expressed in rectal cancer tissues and high expression of SREBF2 was associated with favorable prognosis. Multivariate analysis showed that SREBF2 was an independent prognostic factor, and we integrated it with other clinical factors to establish an effective prognostic nomogram. SREBF2 also played a synergistic role with its co-expressed genes in the prognostic process of rectal cancer. Furthermore, SREBF2 was demonstrated to be closely associated with multiple immune infiltrating cells, and immunotherapy-related genes and may be used to predict the response to immunotherapy.

CONCLUSION

Our study suggests that LMAGs may serve as promising biomarkers in nCRT combined with immunotherapy for rectal cancer. However, large-scale clinical trials and biological experiments are necessary to demonstrate the efficacy and underlying mechanisms.

Intratumor heterogeneity and cell secretome promote chemotherapy resistance and progression of colorectal cancer

The major underlying cause for the high mortality rate in colorectal cancer (CRC) relies on its drug resistance, to which intratumor heterogeneity (ITH) contributes substantially. CRC tumors have been reported to comprise heterogeneous populations of cancer cells that can be grouped into 4 consensus molecular subtypes (CMS). However, the impact of inter-cellular interaction between these cellular states on the emergence of drug resistance and CRC progression remains elusive. Here, we explored the interaction between cell lines belonging to the CMS1 (HCT116 and LoVo) and the CMS4 (SW620 and MDST8) in a 3D coculture model, mimicking the ITH of CRC. The spatial distribution of each cell population showed that CMS1 cells had a preference to grow in the center of cocultured spheroids, while CMS4 cells localized at the periphery, in line with observations in tumors from CRC patients. Cocultures of CMS1 and CMS4 cells did not alter cell growth, but significantly sustained the survival of both CMS1 and CMS4 cells in response to the front-line chemotherapeutic agent 5-fluorouracil (5-FU). Mechanistically, the secretome of CMS1 cells exhibited a remarkable protective effect for CMS4 cells against 5-FU treatment, while promoting cellular invasion. Secreted metabolites may be responsible for these effects, as demonstrated by the existence of 5-FU induced metabolomic shifts, as well as by the experimental transfer of the metabolome between CMS1 and CMS4 cells. Overall, our results suggest that the interplay between CMS1 and CMS4 cells stimulates CRC progression and reduces the efficacy of chemotherapy.

Cancer secretome: finding out hidden messages in extracellular secretions

Secretome analysis has gained popularity recently as a very well-designed proteomic approach that is being used to study various interactions and their effects on cellular activity. This analysis is especially helpful while studying the effects of the cells on their microenvironment, paracrine and autocrine processes, their therapeutic purposes, and as a new diagnostic perspective. Cancer is a condition rather than a specific type of disease and is still yet to be fully understood. Cancer secretome is a fairly new concept that is being implemented to examine the interactions taking place in the tumor microenvironment and can help to understand the phenomena like induction of tumorigenesis, stimulation of immune cells, etc. The secretome analysis helps to gain a different perspective on the existing knowledge on cancer and its effects. The recent advances in secretome studies are directed toward secreted components as drug targets, biomarkers, and companion tools for diagnostic and prognostic purposes in cancer. This review aims to find the interactors in different types of cancer and understand the existing unstructured secretome data and its application in prognosis, diagnosis, and in biomarker study.

RecQ Helicase Somatic Alterations in Cancer

Named the “caretakers” of the genome, RecQ helicases function in several pathways to maintain genomic stability and repair DNA. This highly conserved family of enzymes consist of five different proteins in humans: RECQL1, BLM, WRN, RECQL4, and RECQL5. Biallelic germline mutations in BLM, WRN, and RECQL4 have been linked to rare cancer-predisposing syndromes. Emerging research has also implicated somatic alterations in RecQ helicases in a variety of cancers, including hematological malignancies, breast cancer, osteosarcoma, amongst others. These alterations in RecQ helicases, particularly overexpression, may lead to increased resistance of cancer cells to conventional chemotherapy. Downregulation of these proteins may allow for increased sensitivity to chemotherapy, and, therefore, may be important therapeutic targets. Here we provide a comprehensive review of our current understanding of the role of RecQ DNA helicases in cancer and discuss the potential therapeutic opportunities in targeting these helicases.

Gene-expression profiles of pretreatment biopsies predict complete response of rectal cancer patients to preoperative chemoradiotherapy

Purpose

Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.

Experimental design

We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.

Results

A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).

Conclusion

The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.

Translational relevance

Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.

Exome and Tissue-Associated Microbiota as Predictive Markers of Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer

The clinical and pathological responses to multimodal neoadjuvant therapy in locally advanced rectal cancers (LARCs) remain unpredictable, and robust biomarkers are still lacking. Recent studies have shown that tumors present somatic molecular alterations related to better treatment response, and it is also clear that tumor-associated bacteria are modulators of chemotherapy and immunotherapy efficacy, therefore having implications for long-term survivorship and a good potential as the biomarkers of outcome. Here, we performed whole exome sequencing and 16S ribosomal RNA (rRNA) amplicon sequencing from 44 pre-treatment LARC biopsies from Argentinian and Brazilian patients, treated with neoadjuvant chemoradiotherapy or total neoadjuvant treatment, searching for predictive biomarkers of response (responders, n = 17; non-responders, n = 27). In general, the somatic landscape of LARC was not capable to predict a response; however, a significant enrichment in mutational signature SBS5 was observed in non-responders (p = 0.0021), as well as the co-occurrence of APC and FAT4 mutations (p < 0.05). Microbiota studies revealed a similar alpha and beta diversity of bacteria between response groups. Yet, the linear discriminant analysis (LDA) of effect size indicated an enrichment of Hungatella, Flavonifractor, and Methanosphaera (LDA score ≥3) in the pre-treatment biopsies of responders, while non-responders had a higher abundance of Enhydrobacter, Paraprevotella (LDA score ≥3) and Finegoldia (LDA score ≥4). Altogether, the evaluation of these biomarkers in pre-treatment biopsies could eventually predict a neoadjuvant treatment response, while in post-treatment samples, it could help in guiding non-operative treatment strategies.

Nucleic acid-based markers of response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

The progress that has been made in the treatment of rectal cancer has mostly resulted from multimodality strategy approach that combines surgery, chemotherapy and radiotherapy. In locally advanced rectal cancer (LARC), surgery remains the primary treatment, while neoadjuvant chemoradiotherapy (nCRT) is used to downsize or downstage the tumor before surgical resection. Highly variable response to nCRT observed in LARC patients raises the need for biomarkers to enable prediction and evaluation of treatment response in a more efficient and timely manner than currently available tools. The search for predictive biomarkers continues beyond blood proteins, which have failed in subsequent validation studies. This review presents nucleic acids-based markers and their predictive potential in LARC patients. Most of the candidate biomarkers come from relatively small single-institution studies. The only candidate biomarker that emerged as relevant in more than a single study was elevated levels of Fusobacterium nucleatum nucleic acids in tumor tissue. Considering that this marker is easily accessible through non-invasive analysis of faecal samples, its predictive potential is worth further validation. The other candidate nucleic acid-based biomarkers require more consistent studies on larger cohorts before they can be considered for use in clinical setting.

Validation of microRNA-199b as A Promising Predictor of Outcome and Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer Patients

Simple Summary

The clinical management of locally advanced rectal cancer (LARC) patients would benefit for the establishment of molecular markers that could anticipate the response to neoadjuvant chemoradiotherapy (CRT). We aimed here to validate in an independent cohort our previous findings about the prognostic value showed by miR-199b in LARC as well as to explore its status in the disease progression. Notably, we confirmed in this work that miR-199b has a predictive value of both outcome and response to preoperative CRT in LARC patients further strengthen its potential usefulness in this disease.

Abstract

The absence of established predictive markers with value to anticipate response to neoadjuvant 5-fluorouracil (5-FU)-based chemoradiotherapy (CRT) represents a current major challenge in locally advanced rectal cancer (LARC). The tumor suppressor microRNA (miR)-199b has been reported to play a key role determining 5-FU sensitivity of colorectal cancer cells through the regulation of several signaling pathways, and has emerged as a novel molecular target to overcome the 5-FU resistant phenotype. Moreover, miR-199b downregulation was described as a common alteration that predicts lack of response to preoperative CRT in LARC but this issue needs to be confirmed in independent larger cohorts. Here, we evaluate the clinical impact of miR-199b in LARC and perform additional analyses to further clarify its potential relevance as novel marker in this disease. Thus, miR-199b expression was quantified by real-time-PCR in a cohort of 185 LARC patients, observing this miR downregulated in 22.2% of cases and significantly associated with higher tumor size (p = 0.026) and positive lymph node after CRT (p = 0.005), and higher pathological stage (p = 0.004). Notably, this alteration showed a strong independent predictive value of poor pathological response to neoadjuvant CRT (p = 0.004). Moreover, the subgroup of cases with low miR-199b levels had a markedly shorter overall (p < 001) and event-free survival (p < 0.001), and multivariate analyses showed that miR-199b deregulation represents an independent prognosticator for patient outcome in LARC. Interestingly, the prognostic impact of this miR was strongly significant in both younger and elderly patients, and was very effective determining patient recurrence (p = 0.004). Finally, we compared miR-199b expression profiles in a set of cases with pre and post-treatment samples available, observing that only a minimal response leads to miR-199b increase levels, further suggesting its potential clinical and therapeutic relevance as a promising marker and novel molecular target for the management of LARC.

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer

Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of patients with LARC shows a complete response after CRT. The use of pre-treatment MRI as predictive biomarker could help to increase the chance of organ preservation by tailoring the neoadjuvant treatment. We present a novel machine learning model combining pre-treatment MRI-based clinical and radiomic features for the early prediction of treatment response in LARC patients. MRI scans (3.0 T, T2-weighted) of 72 patients with LARC were included. Two readers independently segmented each tumor. Radiomic features were extracted from both the “tumor core” (TC) and the “tumor border” (TB). Partial least square (PLS) regression was used as the multivariate, machine learning, algorithm of choice and leave-one-out nested cross-validation was used to optimize hyperparameters of the PLS. The MRI-Based “clinical-radiomic” machine learning model properly predicted the treatment response (AUC = 0.793, p = 5.6 × 10^–5). Importantly, the prediction improved when combining MRI-based clinical features and radiomic features, the latter extracted from both TC and TB. Prospective validation studies in randomized clinical trials are warranted to better define the role of radiomics in the development of rectal cancer precision medicine.

Comprehensive Analysis of DNA Methylation and Prediction of Response to NeoadjuvantTherapy in Locally Advanced Rectal Cancer

The treatment for locally advanced rectal carcinomas (LARC) is based on neoadjuvant chemoradiotherapy (nCRT) and surgery, which results in pathological complete response (pCR) in up to 30% of patients. Since epigenetic changes may influence response to therapy, we aimed to identify DNA methylation markers predictive of pCR in LARC patients treated with nCRT. We used high-throughput DNA methylation analysis of 32 treatment-naïve LARC biopsies and five normal rectal tissues to explore the predictive value of differentially methylated (DM) CpGs. External validation was carried out with The Cancer Genome Atlas-Rectal Adenocarcinoma (TCGA-READ 99 cases). A classifier based on three-CpGs DM (linked to OBSL1, GPR1, and INSIG1 genes) was able to discriminate pCR from incomplete responders with high sensitivity and specificity. The methylation levels of the selected CpGs confirmed the predictive value of our classifier in 77 LARCs evaluated by bisulfite pyrosequencing. Evaluation of external datasets (TCGA-READ, GSE81006, GSE75546, and GSE39958) reproduced our results. As the three CpGs were mapped near to regulatory elements, we performed an integrative analysis in regions associated with predicted cis-regulatory elements. A positive and inverse correlation between DNA methylation and gene expression was found in two CpGs. We propose a novel predictive tool based on three CpGs potentially useful for pretreatment screening of LARC patients and guide the selection of treatment modality.

The Role of Micro-RNAs and Circulating Tumor Markers as Predictors of Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

The response to neoadjuvant chemoradiation (nCRT) is a critical step in the management of locally advanced rectal cancer (LARC) patients. Only a minority of LARC patients responds completely to neoadjuvant treatments, thus avoiding invasive radical surgical resection. Moreover, toxic side effects can adversely affect patients' survival. The difficulty in separating in advances responder from non-responder patients affected by LARC highlights the need for valid biomarkers that guide clinical decision-making. In this context, microRNAs (miRNAs) seem to be promising candidates for predicting LARC prognosis and/or therapy response, particularly due to their stability, facile detection, and disease-specific expression in human tissues, blood, serum, or urine. Although a considerable number of studies involving potential miRNA predictors to nCRT have been conducted over the years, to date, the identification of the perfect miRNA signatures or single miRNA, as well as their use in the clinical practice, is still representing a challenge for the management of LARC patients. In this review, we will first introduce LARC and its difficult management. Then, we will trace the scientific history and the key obstacles for the identification of specific miRNAs that predict responsiveness to nCRT. There is a high potential to identify non-invasive biomarkers that circulate in the human bloodstream and that might indicate the LARC patients who benefit from the watch-and-wait approach. For this, we will critically evaluate recent advances dealing with cell-free nucleic acids including miRNAs and circulating tumor cells as prognostic or predictive biomarkers.

Secreted amphiregulin promotes vincristine resistance in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer. Despite advances in surgery, radiotherapy and chemotherapy, the overall 5‑year survival rate of patients with OSCC has not significantly improved. In addition, the prognosis of patients with advanced‑stage OSCC remains poor. Therefore, it is necessary to develop novel therapeutic modalities. Vincristine (VCR), a naturally occurring vinca alkaloid, is a classical microtubule‑destabilizing agent and is widely used in the treatment of a number of cancers. Despite the proven antitumor benefits of VCR treatment, one of the major reasons for the failure of treatment is drug resistance. Changes in the tumor microenvironment are responsible for cross‑talk between cells, which may facilitate drug resistance in cancers; secreted proteins may promote communication between cancer cells to induce the development of resistance. To identify the secreted proteins involved in VCR resistance, conditioned media was obtained, and an antibody array was conducted to screen a comprehensive secretion profile between VCR‑resistant (SAS‑VCR) and parental (SAS) OSCC cell lines. The results showed that amphiregulin (AREG) was highly expressed and secreted in SAS‑VCR cells. Pretreatment with exogenous recombinant AREG markedly increased drug resistance against VCR in OSCC cells, as assessed by an MTT assay. Colony formation, MTT and western blot assays were performed to investigate the effects of AREG knockdown on VCR sensitivity. The results indicated that AREG expression can regulate VCR resistance in OSCC cells; overexpression of AREG increased VCR resistance in parental cells, whereas AREG knockdown decreased the VCR resistance of resistant cells. In addition, it was also demonstrated that the glycogen synthase kinase‑3β pathway may be involved in AREG‑induced VCR resistance. These findings may provide rationale to combine VCR with blockade of AREG‑related pathways for the effective treatment of OSCC.