Rectal cancer is a heterogeneous disease at the genetic and molecular levels, both aspects having major repercussions on the tumor immune contexture. Whilst microsatellite status and tumor mutational load have been associated with response to immunotherapy, presence of tumor-infiltrating lymphocytes is one of the most powerful prognostic and predictive biomarkers. Yet, the majority of rectal cancers are characterized by microsatellite stability, low tumor mutational burden and poor T cell infiltration. Consequently, these tumors do not respond to immunotherapy and treatment largely relies on radiotherapy alone or in combination with chemotherapy followed by radical surgery. Importantly, pre-clinical and clinical studies suggest that radiotherapy can induce a complete reprograming of the tumor microenvironment, potentially sensitizing it for immune checkpoint inhibition. Nonetheless, growing evidence suggest that this synergistic effect strongly depends on radiotherapy dosing, fractionation and timing. Despite ongoing work, information about the radiotherapy regimen required to yield optimal clinical outcome when combined to checkpoint blockade remains largely unavailable. In this review, we describe the molecular and immune heterogeneity of rectal cancer and outline its prognostic value. In addition, we discuss the effect of radiotherapy on the tumor microenvironment, focusing on the mechanisms and benefits of its combination with immune checkpoint inhibitors.
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http://dx.doi.org/10.3390/cancers13061374 | DOI Listing |
Wiad Lek
January 2025
DEPARTMENT OF GENERAL, ONCOLOGICAL AND DIGESTIVE TRACT SURGERY, MEDICAL CENTRE OF POSTGRADUATE EDUCATION, ORŁOWSKI HOSPITAL, MEDICAL CENTRE OF POSTGRADUATE EDUCATION, WARSAW, POLAND.
The aim of this study is to present a case of laparoscopic treatment of perineal hernia in a patient after abdominoperineal resection od the rectum. We present the case of a 63-year-old woman who was operated on laparoscopically with a mesh sewn in at the level of the sacrum, iliac vessels and pubic symphysis. And covered with a peritoneal flap above the urinary bladder.
View Article and Find Full Text PDFAsian Pac J Cancer Prev
January 2025
Department of Pathology, Phramongkutklao College of Medicine, Thailand.
Objective: To determine the correlation among five different types of tumor regression grading (TRG) systems. Test-retest reliability analyses were conducted at two time points to assess the internal validity and consistency of these five TRG systems.
Methods: A test-retest study was performed in 34 pathologically confirmed rectal adenocarcinoma specimens.
Urol Res Pract
January 2025
Department of Urology, Universitas Sumatera Utara Hospital - Universitas Sumatera Utara, Indonesia.
Improved prostate biopsy procedures have been developed to overcome traditional limitations, aiming to enhance cancer diagnosis accuracy. To assess the existing knowledge of the effectiveness and risks linked to transperineal (TP) vs. transrectal (TR) prostate biopsy.
View Article and Find Full Text PDFWorld J Gastrointest Surg
January 2025
Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China.
Early recurrence (ER) following surgery for rectal cancer is a significant factor impacting patient survival rates. Tsai identified age, preoperative neoadjuvant therapy, length of hospital stay, tumour location, and pathological stage as factors influencing the risk of ER. Postoperative monitoring for ER should encompass a thorough medical history review, physical examination, tumour marker testing, and imaging studies.
View Article and Find Full Text PDFWorld J Gastrointest Surg
January 2025
Department of Minimally Invasive Digestive Surgery, Antoine-Béclère Hospital, Assistance Publique-Hôpitaux de ParisClamart 92140, Haute-Seine, France.
Anastomotic leakage (AL) is a significant complication following rectal cancer surgery, adversely affecting both quality of life and oncological outcomes. Recent advancements in artificial intelligence (AI), particularly machine learning and deep learning, offer promising avenues for predicting and preventing AL. These technologies can analyze extensive clinical datasets to identify preoperative and perioperative risk factors such as malnutrition, body composition, and radiological features.
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