Predictive value of Smac, VEGF and Ki-67 in rectal cancer treated with neoadjuvant therapy

Expression of vascular endothelial growth factor as a predictor of complete response for preoperative chemoradiotherapy in rectal cancer

Biomarkers that predict tumor response before surgical treatment are necessary to help select patients for preoperative chemoradiotherapy for rectal cancer. However, no definite predictive biomarker has been established. This study explored programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), p-signal transducer and activator of transcription 3 (p-STAT3), and death-domain associated protein as predictive biomarkers with regard to preoperative chemoradiotherapy in rectal cancer.Formalin-fixed paraffin-embedded cancer tissues from pretreatment biopsies from 31 patients who underwent preoperative chemoradiotherapy were studied. The biomarkers were evaluated by immunohistochemistry.PD-L1 positivity was found in 22.6% of 31 patients and complete response (CR) showed 33.3% and non-CR showed 18.2%. EGFR positivity was found in 71.0% of 31 patients and CR showed 88.9% and non-CR showed 73.6%. VEGF positivity was found in 83.9% of 31 patients and CR showed 88.9% and non-CR showed 81.8%. p-STAT3 positivity was found in 80.6% of 31 patients and CR showed 88.9% and non-CR showed 77.3%. On multiple logistic regression analysis, only VEGF expression was found to be a significant predictive factor for CR (P = .001). VEGF expression in pretreatment biopsies might be a predictive marker for CR after preoperative chemoradiation in rectal cancer.Although there is a restriction of small sample size, our finding suggested that this study can be foundation for a larger further study for biomarkers which can predict neoadjuvant therapy response of specimens obtained for diagnosis before surgery.

Network Mapping of Molecular Biomarkers Influencing Radiation Response in Rectal Cancer

Preoperative radiotherapy (RT) plays an important role in the management of locally advanced rectal cancer (RC). Tumor regression after RT shows marked variability, and robust molecular methods are needed to help predict likely response. The aim of this study was to review the current published literature and use Gene Ontology (GO) analysis to define key molecular biomarkers governing radiation response in RC. A systematic review of electronic bibliographic databases (Medline, Embase) was performed for original articles published between 2000 and 2015. Biomarkers were then classified according to biological function and incorporated into a hierarchical GO tree. Both significant and nonsignificant results were included in the analysis. Significance was binarized on the basis of univariate and multivariate statistics. Significance scores were calculated for each biological domain (or node), and a direct acyclic graph was generated for intuitive mapping of biological pathways and markers involved in RC radiation response. Seventy-two individual biomarkers across 74 studies were identified. On highest-order classification, molecular biomarkers falling within the domains of response to stress, cellular metabolism, and pathways inhibiting apoptosis were found to be the most influential in predicting radiosensitivity. Homogenizing biomarker data from original articles using controlled GO terminology demonstrated that cellular mechanisms of response to RT in RC-in particular the metabolic response to RT-may hold promise in developing radiotherapeutic biomarkers to help predict, and in the future modulate, radiation response.

Predicting the pathological response to neoadjuvant chemoradiation using untargeted metabolomics in locally advanced rectal cancer

PURPOSE

The present study aimed to identify a panel of potential metabolite biomarkers to predict tumor response to neoadjuvant chemo-radiation therapy (NCRT) in locally advanced rectal cancer (LARC).

EXPERIMENTAL DESIGN

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics was used to profile human serum samples (n = 106) from LARC patients treated with NCRT. The samples were collected from Fudan University Shanghai Cancer Center (FUSCC) from July 2014 to January 2016. Statistical methods, such as partial least squares (PLS) and Wilcoxon rank-sum test, were used to identify discriminative metabolites between NCRT-sensitive and NCRT-resistant patients according to their tumor regression grade (TRG). This trial is registered with Clinical Trials.gov, number NCT03149978.

RESULTS

A panel of metabolites was selected as potential predictive biomarkers of pathological response to NCRT. A total of 4810 metabolic peaks were detected, and 57 significantly dysregulated peaks were identified. These 57 metabolic peaks were used to differentiate patients using PLS in a dataset containing NCRT-sensitive (n = 56) and NCRT-resistant (n = 49) patients. The combination of 57 metabolic peaks had AUC values of 0.88, 0.81 and 0.84 in the prediction models using PLS, random forest, and support vector machine, respectively, suggesting that metabolomics has the potential ability to predict responses to NCRT. Furthermore, 15 metabolite biomarkers were identified and used to construct a logistic regression model and explore dysregulated metabolic pathways using untargeted metabolic profiling and data mining approaches.

CONCLUSIONS

A panel of metabolites has been identified to facilitate the prediction of tumor response to NCRT in LARC, which is promising for the generation of personalized treatment strategies for LARC patients.

Esophageal adenocarcinoma microenvironment: Peritumoral adipose tissue effects associated with chemoresistance

Peritumoral microenvironment affects cancer development and chemoresistance, and visceral adipose tissue may play a critical role. We aimed to identify depot‐specific adipose characteristics associated with carcinogenesis and resistance to neoadjuvant therapy in esophageal adenocarcinoma (EAC). We analyzed: (i) the peritumoral adipose tissue of rats following the induction of esophageal carcinogenesis; (ii) the peritumoral and distal (omental) adipose tissue of patients affected by EAC; (iii) adipose‐derived stem cells (ADSC) isolated from healthy patients and treated with conditioned medium (CM), collected from tumoral and adipose tissue of patients with EAC. In peritumoral adipose tissue of rats, CD34, CD31 and vascular endothelial growth factor (VEGF) expression increased progressively during EAC development. In patients with EAC, expression of CD34, CD45, CD90 and nucleostemin (NSTM) was higher in peritumoral than in distal adipose tissue and decreased in the presence of neoadjuvant therapy. Moreover, expression of NSTM, octamer‐binding transcription factor 4 (OCT‐4) and VEGF was higher in peritumoral (but not in distal) adipose tissue of chemoresistant patients. In ADSC, treatment with peritumoral adipose tissue CM increased the adipogenic potential and the expression of CD34, CD90, NSTM and OCT‐4. These effects were similar to those induced by cancer‐derived CM, but were not observed in ADSC treated with distal adipose tissue CM and were partially reduced by a leptin antagonist. Last, ADSC treated with peritumoral CM of chemoresistant patients displayed increased expression of NSTM, OCT‐4, leptin, leptin receptor, alpha‐smooth muscle actin (α‐SMA), CD34 and VEGF. These results suggest that peritumoral adipose tissue may promote, by paracrine signaling, the expression of depot‐specific factors associated with therapeutic resistance.

Predictive and prognostic biomarkers for neoadjuvant chemoradiotherapy in locally advanced rectal cancer

Locally advanced rectal cancer is regularly treated with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy. There is a need for biomarkers to assess treatment response, and aid in stratification of patient risk to adapt and personalise components of the therapy. Currently, pathological stage and tumour regression grade are used to assess response. Experimental markers include proteins involved in cell proliferation, apoptosis, angiogenesis, the epithelial to mesenchymal transition and microsatellite instability. As yet, no single marker is sufficiently robust to have clinical utility. Microarrays that screen a tumour for multiple promising candidate markers, gene expression and microRNA profiling will likely have higher yield and it is expected that a combination or panel of markers would prove most useful. Moving forward, utilising serial samples of circulating tumour cells or circulating nucleic acids can potentially allow us to demonstrate tumour heterogeneity, document mutational changes and subsequently measure treatment response.

Can a biomarker-based scoring system predict pathologic complete response after preoperative chemoradiotherapy for rectal cancer?

BACKGROUND

Numerous molecular markers have been investigated as potential predictors of tumor responses to preoperative chemoradiotherapy (preCRT) for rectal cancer.

OBJECTIVE

To develop a system in which biomarkers are used to predict the likelihood of a pathologic complete response (pCR) to preCRT.

DESIGN & SETTING

This is a retrospective analysis of tumor specimens collected prior to preCRT from 81 patients who underwent curative resection for primary rectal adenocarcinoma between June 2008 and February 2012.

MAIN OUTCOME MEASURES

Using tissue microarrays and immunohistochemistry, expression levels of twelve candidate biomarkers (p53, p21, Bcl2, Bax, EGFR, Cox-2, MLH-1, MSH-2, Ku70, VEGF, TS, Ki-67) were evaluated in paraffin-embedded tumor samples collected before preCRT. The correlation between biomarker expression levels and the pathologic response to preCRT was assessed based on histopathological staging (pTNM) and tumor regression grade (TRG).

RESULTS

Expression levels of 4 biomarkers (p53, VEGF, p21, Ki67) correlated with pCR. Patients showing low expression of p53 and/or high expression of VEGF, p21, and Ki67 exhibited a significantly greater pCR rate. A scoring system devised so that one point was given for each biomarker whose expression level correlated with pCR (score range: 0-4) showed that 1 of 26 patients with scores of 0 to 1 achieved pCR, whereas 26 of 55 patients with scores of 2 to 4 achieved pCR (3.8% vs. 47.3%, p < 0.001). For prediction of pCR, the scoring system showed 96.3% sensitivity, 46.3% specificity, a 47.3% positive predictive value, and a 96.2% negative predictive value.

LIMITATIONS

Immunohistochemistry has limitations related to reproducibility and the ability to provide quantitative information. In addition, this study lacks test and validation sets.

CONCLUSIONS

Expression levels of 4 biomarkers correlated with pCR after preCRT for rectal cancer. A scoring system based on levels of biomarker expression showed good sensitivity and negative predictive value for pCR.

Future directions in combined modality therapy for rectal cancer: reevaluating the role of total mesorectal excision after chemoradiotherapy

Most patients who develop rectal cancer present with locoregionally advanced (T3 or node-positive) disease. The standard management of locoregionally advanced rectal cancer is neoadjuvant concurrent chemoradiotherapy (nCRT), followed by radical resection (low-anterior resection or abdominoperineal resection with total mesorectal excision). Approximately 15% of patients can have a pathologic complete response (pCR) at the time of surgery, indicating that some patients can have no detectable residual disease after nCRT. The actual benefit of surgery in this group of patients is unclear. It is possible that omission of surgery in these patients, termed selective nonoperative management, can limit the toxicities associated with standard, multimodal combined modality therapy without compromising disease control. In this review, we discuss the clinical experiences to date using selective nonoperative management and various attempts at escalation of nCRT to improve the number of patients who have a pCR. We also explore several clinical, laboratory, imaging, histopathologic, and genetic biomarkers that have been tested as tools to predict which patients are most likely to have a pCR after nCRT.