Recent Advances in Targeted Therapies for Advanced Gastrointestinal Malignancies

MiR-17-5p Targets and Downregulates CADM2, Activating the Malignant Phenotypes of Colon Cancer Cells

Accumulating studies have demonstrated that CADM2 modulated malignant phenotype of various cancer cells, while its regulatory function and mechanism have not yet been reported. In this study, qRT-PCR was utilized to measure CADM2 mRNA level in normal cells and colon cancer cells, also, IHC and WB were applied to detect CADM2 protein expression in colon tissues, exhibiting low mRNA and protein levels of CADM2 in colon cancer. Applying cell function experiments, the impacts of CADM2 on colon cell phenotypes were examined, and the results illustrated that upregulating CADM2 remarkably repressed proliferation, invasion, migration, cell cycle of colon cancer cells, and facilitated cell apoptosis. Thus, it could be considered that CADM2 served as a tumor repressor gene in colon cancer. Moreover, the outcomes of dual-luciferase assay displayed that miR-17-5p could target CADM2, and overexpressing miR-17-5p could notably inhibit the mRNA and protein expression levels of CADM2. We, therefore, assumed that CADM2 was a downstream target of miR-139-5p. qRT-PCR was conducted to assess miR-17-5p level in colon cancer cells and normal cells, verifying a high miR-17-5p expression in the cancer cells. The effects of miR-17-5p on colon cell phenotypes were examined as well, where we determined that miR-17-5p served as a tumor-promoting factor. Finally, the rescue experiments exhibited that miR-17-5p could activate tumor-promoting phenotypes, while such activating effects could be reversed by upregulating CADM2. In short, the study proved that miR-17-5p facilitated malignant progression of colon cancer through targeting CADM2 at a post-transcriptional level. Our findings offer new insight into molecular therapy of colon cancer patients.

A multicenter clinical study: personalized medication for advanced gastrointestinal carcinomas with the guidance of patient-derived tumor xenograft (PDTX)

BACKGROUND

Establish patient-derived tumor xenograft (PDTX) from advanced GICs and assess the clinical value and applicability of PDTX for the treatment of advanced gastrointestinal cancers.

METHODS

Patients with advanced GICs were enrolled in a registered multi-center clinical study (ChiCTR-OOC-17012731). The performance of PDTX was evaluated by analyzing factors that affect the engraftment rate, comparing the histological consistency between primary tumors and tumorgrafts, examining the concordance between the drug effectiveness in PDTXs and clinical responses, and identifying genetic variants and other factors associated with prognosis.

RESULTS

Thirty-three patients were enrolled in the study with the engraftment rate of 75.8% (25/33). The success of engraftment was independent of age, cancer types, pathological stages of tumors, and particularly sampling methods. Tumorgrafts retained the same histopathological characteristics as primary tumors. Forty-nine regimens involving 28 drugs were tested in seventeen tumorgrafts. The median time for drug testing was 134.5 days. Follow-up information was obtained about 10 regimens from 9 patients. The concordance of drug effectiveness between PDTXs and clinical responses was 100%. The tumor mutation burden (TMB) was correlated with the effectiveness of single drug regimens, while the outgrowth time of tumorgrafts was associated with the effectiveness of combined regimens.

CONCLUSION

The engraftment rate in advanced GICs was higher than that of other cancers and meets the acceptable standard for applying personalized therapeutic strategies. Tumorgrafts from PDTX kept attributes of the primary tumor. Predictions from PDTX modeling closely agreed with clinical drug responses. PDTX may already be clinically applicable for personalized medication in advanced GICs.

Scope of Artificial Intelligence in Gastrointestinal Oncology

Gastrointestinal cancers are among the leading causes of death worldwide, with over 2.8 million deaths annually. Over the last few decades, advancements in artificial intelligence technologies have led to their application in medicine. The use of artificial intelligence in endoscopic procedures is a significant breakthrough in modern medicine. Currently, the diagnosis of various gastrointestinal cancer relies on the manual interpretation of radiographic images by radiologists and various endoscopic images by endoscopists. This can lead to diagnostic variabilities as it requires concentration and clinical experience in the field. Artificial intelligence using machine or deep learning algorithms can provide automatic and accurate image analysis and thus assist in diagnosis. In the field of gastroenterology, the application of artificial intelligence can be vast from diagnosis, predicting tumor histology, polyp characterization, metastatic potential, prognosis, and treatment response. It can also provide accurate prediction models to determine the need for intervention with computer-aided diagnosis. The number of research studies on artificial intelligence in gastrointestinal cancer has been increasing rapidly over the last decade due to immense interest in the field. This review aims to review the impact, limitations, and future potentials of artificial intelligence in screening, diagnosis, tumor staging, treatment modalities, and prediction models for the prognosis of various gastrointestinal cancers.

Antibody drug conjugates in gastrointestinal cancer: From lab to clinical development

The antibody-drug conjugates (ADCs) are one the fastest growing biotherapeutics in oncology and are still in their infancy in gastrointestinal (GI) cancer for clinical applications to improve patient survival. The ADC based approach is developed with tumor specific antigen, antibody carrying cytotoxic agents to precisely target and deliver chemotherapeutics at the tumor site. To date, 11 ADCs have been approved by US-FDA, and more than 80 are in the clinical development phase for different oncological indications. However, The ADCs based therapies in GI cancers are still far from having high-efficient clinical outcomes. The limited success of these ADCs and lessons learned from the past are now being used to develop a newer generation of ADC against GI cancers. In this review, we did a comprehensive assessment of the key components of ADCs, including tumor marker, antibody, cytotoxic payload, and linkage strategy, with a focus on technical improvement and some future trends in the pipeline for clinical translation. The various preclinical and clinical ADCs used in gastrointestinal malignancies, their target, composition and bioconjugation, along with preclinical and clinical outcomes, are discussed. The emphasis is also given to new generation ADCs employing novel mAb, payload, linker, and bioconjugation methods are also included.

Phase I/II Trial of Vemurafenib in Dogs with Naturally Occurring, BRAF-mutated Urothelial Carcinoma

BRAF-targeted therapies including vemurafenib (Zelboraf) induce dramatic cancer remission; however, drug resistance commonly emerges. The purpose was to characterize a naturally occurring canine cancer model harboring complex features of human cancer, to complement experimental models to improve BRAF-targeted therapy. A phase I/II clinical trial of vemurafenib was performed in pet dogs with naturally occurring invasive urothelial carcinoma (InvUC) harboring the canine homologue of human BRAF ^V600E The safety, MTD, pharmacokinetics, and antitumor activity were determined. Changes in signaling and immune gene expression were assessed by RNA sequencing and phosphoproteomic analyses of cystoscopic biopsies obtained before and during treatment, and at progression. The vemurafenib MTD was 37.5 mg/kg twice daily. Anorexia was the most common adverse event. At the MTD, partial remission occurred in 9 of 24 dogs (38%), with a median progression-free interval of 181 days (range, 53-608 days). In 18% of the dogs, new cutaneous squamous cell carcinoma and papillomas occurred, a known pharmacodynamic effect of vemurafenib in humans. Upregulation of genes in the classical and alternative MAPK-related pathways occurred in subsets of dogs at cancer progression. The most consistent transcriptomic changes were the increase in patterns of T lymphocyte infiltration during the first month of vemurafenib, and of immune failure accompanying cancer progression. In conclusion, the safety, antitumor activity, and cutaneous pharmacodynamic effects of vemurafenib, and the development of drug resistance in dogs closely mimic those reported in humans. This suggests BRAF-mutated canine InvUC offers an important complementary animal model to improve BRAF-targeted therapies in humans.

Landscape of Current Targeted Therapies for Advanced Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequent and lethal cancer types worldwide. While surgery with chemotherapy and radiotherapy remains the only curative approach for localized CRC, for metastatic disease the therapeutic landscape has significantly evolved over the last years. Development and approval of novel targeted therapies, such as monoclonal antibodies against EGFR and VEGF, have significantly increased the median survival of patients with metastatic disease, with some trials reporting a benefit over 40 months. Increasing accessibility of high throughput sequencing has unraveled several new therapeutic targets. Actionable alterations, such as HER2 overexpression, BRAF mutations, and NTRK fusions, are currently available in metastatic disease, providing significant therapeutic opportunities for these patients, while new emerging agents, as immune checkpoint inhibitors, promise better treatment options in the near future. In this chapter, an overview of established and future CRC targeted therapies in the clinical setting is provided, as well as their mechanism of action, limitations, and future applicability.

Combination of Anti-EGFR and Anti-VEGF Drugs for the Treatment of Previously Treated Metastatic Colorectal Cancer: A Case Report and Literature Review

The standard third-line treatment of metastatic colorectal cancer (mCRC) includes the small-molecule anti-vascular drugs (Regofenib and Fruquintinib) and the chemotherapy drug trifluridine and tipiracil hydrochloride (TAS-102). There is no standard treatment for mCRC if the third-line treatment failed. Therefore, it is a pressing need to develop new therapeutic approaches to improve the survival of patients who developed drug resistance to the third-line treatment. In this study, we report a case of mCRC with RAS/BRAF wild-type, who was successfully treated using cetuximab in combination with fruquintinib after resistance to chemotherapy, bevacizumab, cetuximab and regorafenib. This patient responded to this combination regimen. Then, we discuss the mechanisms of action of this combination. Furthermore, we introduce the clinical trials on the combination regimens of anti-EGFR with anti-vascular monoclonal antibodies. Finally, we discuss the clinical explorations of using combination of anti-EGFR with small-molecule anti-VEGF drugs and their potential benefits. The clinical effects of small-molecule anti-vascular drugs in combination with anti-EGFR in the treatment of CRC warrant further explored.

Role of Her-2 in Gastrointestinal Tumours beyond Gastric Cancer: A Tool for Precision Medicine

Gastrointestinal (GI) tumors account for a quarter of all the cancer burden and a third of the global cancer-related mortality. Among them, some cancers retain a dismal prognosis; therefore, newer and innovative therapies are urgently needed in priority disease areas of high-unmet medical need. In this context, HER2 could be a relevant prognostic and predictive biomarker acting as a target for specific drugs. However, if the role of HER2 has been object of investigation for several years in gastric cancer, it is not well established in other GI malignancies. The aim of this narrative review was to portray the current landscape of the potential role of HER2 as a predictive biomarker for GI tumors beyond gastric cancer. In colon cancer, the benefit from anti-HER2 therapies is less clear than in gastric neoplasms for the lack of controlled studies. Pancreatic, biliary tract adenocarcinomas and hepatocarcinoma may derive a less clear clinical benefit by using anti-HER2 agents in HER2 positive tumors. Overall, the results are promising and seem to suggest that the integration of multiple modalities of therapies can optimize the cancer care. However, further prospective trials are needed to validate the use of personalized targeted therapies in this field.

Artificial intelligence in gastrointestinal cancer: Recent advances and future perspectives

Artificial intelligence (AI) using machine or deep learning algorithms is attracting increasing attention because of its more accurate image recognition ability and prediction performance than human-aid analyses. The application of AI models to gastrointestinal (GI) clinical oncology has been investigated for the past decade. AI has the capacity to automatically detect and diagnose GI tumors with similar diagnostic accuracy to expert clinicians. AI may also predict malignant potential, such as tumor histology, metastasis, patient survival, resistance to cancer treatments and the molecular biology of tumors, through image analyses of radiological or pathological imaging data using complex deep learning models beyond human cognition. The introduction of AI-assisted diagnostic systems into clinical settings is expected in the near future. However, limitations associated with the evaluation of GI tumors by AI models have yet to be resolved. Recent studies on AI-assisted diagnostic models of gastric and colorectal cancers in the endoscopic, pathological, and radiological fields were herein reviewed. The limitations and future perspectives for the application of AI systems in clinical settings have also been discussed. With the establishment of a multidisciplinary team containing AI experts in each medical institution and prospective studies, AI-assisted medical systems will become a promising tool for GI cancer.