Complete Pathological Response After Neoadjuvant Short-Course Immunotherapy with Ipilimumab and Nivolumab in Locally Advanced MSI-H/dMMR Rectal Cancer

A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer

This study aimed to develop an optimal radiomics model for preoperatively predicting microsatellite instability (MSI) in patients with rectal cancer (RC) based on multiparametric magnetic resonance imaging. The retrospective study included 308 RC patients who did not receive preoperative antitumor therapy, among whom 51 had MSI. Radiomics features were extracted and dimensionally reduced from T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and T1-weighted contrast enhanced (T1CE) images for each patient, and the features of each sequence were combined. Multifactor logistic regression was used to screen the optimal feature set for each combination. Different machine learning methods were applied to construct predictive MSI status models. Relative standard deviation values were determined to evaluate model performance and select the optimal model. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses were performed to evaluate model performance. The model constructed using the k-nearest neighbor (KNN) method combined with T2WI and T1CE images performed best. The area under the curve values for prediction of MSI with this model were 0.849 (0.804-0.887), with a sensitivity of 0.784 and specificity of 0.805. The Delong test showed no significant difference in diagnostic efficacy between the KNN-derived model and the traditional logistic regression model constructed using T1WI + DWI + T1CE and T2WI + T1WI + DWI + T1CE data (P > 0.05) and the diagnostic efficiency of the KNN-derived model was slightly better than that of the traditional model. From ROC curve analysis, the KNN-derived model significantly distinguished patients at low- and high-risk of MSI with the optimal threshold of 0.2, supporting the clinical applicability of the model. The model constructed using the KNN method can be applied to noninvasively predict MSI status in RC patients before surgery based on radiomics features from T2WI and T1CE images. Thus, this method may provide a convenient and practical tool for formulating treatment strategies and optimizing individual clinical decision-making for patients with RC.

Unanticipated pathological clearance in two cases of clinical T4b dMMR/MSI-h advanced colorectal cancer: the potential of immune checkpoint inhibitors despite positive positron-emission tomography results

BACKGROUND

The standard treatment for colorectal cancer consists of surgery and chemotherapy, which can be combined to improve outcomes. Immune checkpoint inhibitors (ICI) are a significant advancement in the standard treatment of metastatic, unresectable colorectal cancer with deficient mismatch repair (dMMR). However, limited data are available about the use of ICI in the neoadjuvant and conversion settings. Here, we present two cases treated with ICI.

CASE PRESENTATION

Case 1: A 75-year-old male with a large, borderline resectable rectal cancer diagnosed as cT4bN1bM0 who underwent neoadjuvant chemotherapy, followed by combination ICI consisting of ipilimumab and nivolumab. After four courses of ICI, the tumor significantly shrank, but positron emission tomography still showed a positive result and R0 resection was performed. Pathological analysis revealed no residual cancer cells. The patient has been monitored without adjuvant chemotherapy, and no recurrences have occurred after one year. Case 2: A 60-year-old male with locally advanced sigmoid colon cancer who received neoadjuvant treatment with pembrolizumab. The tumor partially shrank after three courses, and continued pembrolizumab monotherapy resulted in further tumor shrinkage which still showed positive positron emission tomography. Curative sigmoidectomy with partial resection of the ileum and bladder was performed, and the pathological outcome was pCR. There was no viable tumor in the specimen. The patient has been monitored without adjuvant chemotherapy for six months, and no recurrence has been observed.

CONCLUSIONS

The present study reports two cases, including a large, borderline resectable rectal cancer after failure of chemotherapy followed by combination treatment with nivolumab and ipilimumab and one case of sigmoid colon cancer after pembrolizumab treatment, which resulted in pathological complete response. However, it remains unknown whether ICI therapy can replace surgery or diminish the optimal extent of resection, or whether adjuvant chemotherapy is needed after surgery in the case of achieving pCR after ICI therapy. Overall, this case report suggests that ICI before colorectal surgery can be effective and potentially a 'watch-and-wait" strategy could be used for cases in which ICI is effective.

Neoadjuvant immunotherapy in a locally advanced colon cancer patient with MSI-H and suspected Lynch syndrome: A case report

Carrilizumab, a PD-1 inhibitor, has shown therapeutic effectiveness in patients with late-stage or metastatic solid tumors exhibiting DNA mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H). dMMR/MSI-H cancer patients are known to be responsive to PD-1 inhibitors. However, the use of carrilizumab for preoperative immunotherapy in early, unresectable MSI-H/dMMR primary colon cancer lesions is relatively underexplored. We present the case of a 46-year-old male who sought medical attention at our institution due to a history of hematochezia for two weeks, right-sided abdominal pain for one week, and loose stools. Imaging indicated duodenal involvement, and a biopsy confirmed ascending colon adenocarcinoma with MSI-H status. Given that the patient's family exhibited a history of more than three confirmed cases of colorectal cancer spanning two generations, Lynch syndrome was considered. After four cycles of PD-1 antagonist immunotherapy with carrilizumab, the patient's symptoms resolved, and physical examination revealed no abdominal tenderness or palpable masses. Following radical colectomy, the primary tumor exhibited a pathological complete response. This case highlights the potential of preoperative neoadjuvant immunotherapy to improve staging accuracy and increase surgical resection rates in T4b MSI-H colon cancer patients without distant metastasis, suggesting a need for reconsideration of the treatment approach.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

An integrative clinical and CT-based tumoral/peritumoral radiomics nomogram to predict the microsatellite instability in rectal carcinoma

BACKGROUND

Microsatellite instability (MSI) is detected in approximately 15% of colorectal carcinoma (CRC) patients, which has emerged as a predictor of patient response to adjuvant chemotherapy. Rectal carcinoma (RC) is the most common type of CRC. Therefore, prediction of MSI status of RC is significant for personalized medication. The purpose of this article was to develop an integrative model that combines clinical characteristics and computed tomography-based (CT-based) tumoral/peritumoral radiomics to predict the MSI status in RC.

METHODS

A cohort of 788 RCs with 97 high-MSI status (MSI-H) and 691 microsatellite stable status (MSS) were enrolled between January 2015 and January 2021 in this retrospective study. Clinical characteristics were recorded, and CT-based tumoral/peritumoral radiomic features were calculated after segmenting volume of interests. The patients were randomly divided into training and validation sets in a 7:3 proportion. Logistic models of single tumoral radiomics (LM-tRadio), peritumoral radiomics (LM-ptRadio), and combined tumoral/peritumoral radiomics (LM-Radio) were constructed to distinguish MSI-H from MSS, and a relevant radiomic score was calculated. An integrative nomogram (LM-Nomo) was developed, including significant clinical characteristics and CT-based tumoral/peritumoral radiomics. The area under receiver operator curve (AUC) was calculated to evaluate the efficacy of prediction.

RESULTS

The AUCs of LM-Radio were 0.785 (95%CI 0.732-0.837) in the training set and were 0.628 (95%CI 0.528-0.723) in the validation set, which were higher than those of LM-tRadio and LM-ptRadio. The AUCs of single LM-ptRadio were slightly higher than those of LM-tRadio (0.724 vs. 0.708 in the training set, 0.613 vs. 0.602 in the validation set). The LM-Nomo containing carcinoembryonic antigen (CEA), hypertension, and CT-based tumoral/peritumoral radiomic score showed the highest AUCs of 0.796 (95%CI 0.748-0.843) in the training set and 0.679 (95%CI 0.588-0.771) in the validation set in predicting the MSI-H status of RC.

CONCLUSION

The AUCs of LM-ptRadio were slightly higher than LM-tRadio to evaluate the MSI-H status of RC. The LM-Nomo, which includes significant clinical characteristics and CT-based tumoral/peritumoral radiomics score, demonstrated the best performance in predicting MSI-H status of RC.

Detecting microsatellite instability in colorectal cancer using Transformer-based colonoscopy image classification and retrieval

Colorectal cancer (CRC) is a major global health concern, with microsatellite instability-high (MSI-H) being a defining characteristic of hereditary nonpolyposis colorectal cancer syndrome and affecting 15% of sporadic CRCs. Tumors with MSI-H have unique features and better prognosis compared to MSI-L and microsatellite stable (MSS) tumors. This study proposed establishing a MSI prediction model using more available and low-cost colonoscopy images instead of histopathology. The experiment utilized a database of 427 MSI-H and 1590 MSS colonoscopy images and vision Transformer (ViT) with different feature training approaches to establish the MSI prediction model. The accuracy of combining pre-trained ViT features was 84% with an area under the receiver operating characteristic curve of 0.86, which was better than that of DenseNet201 (80%, 0.80) in the experiment with support vector machine. The content-based image retrieval (CBIR) approach showed that ViT features can obtain a mean average precision of 0.81 compared to 0.79 of DenseNet201. ViT reduced the issues that occur in convolutional neural networks, including limited receptive field and gradient disappearance, and may be better at interpreting diagnostic information around tumors and surrounding tissues. By using CBIR, the presentation of similar images with the same MSI status would provide more convincing deep learning suggestions for clinical use.

A pathological complete response after immunotherapy with pembrolizumab for distal duodenal adenocarcinoma caused by Lynch syndrome: a case report

Primary adenocarcinoma of the duodenum is a rare neoplasm that is often microsatellite instability-high (MSI-H). Pembrolizumab, a monoclonal antibody, has been recently approved in Japan for treatment of MSI-H solid tumors. Lynch syndrome is a frequent hereditary cancer predisposition syndrome. It is linked to an increased risk of various types of cancer, including colorectal and endometrial cancer, and is closely related to MSI-H. We present the case of a 55-year-old woman who was diagnosed with duodenal cancer. Biopsy findings revealed MSI-H, and pembrolizumab therapy was initiated because the tumor was in contact with the left renal vein and had metastasized to the mesenteric lymph nodes of the small intestine. Subsequently, after completing two courses of pembrolizumab therapy, the patient developed duodenal stenosis and underwent surgery. Pathological analysis of the resected specimen revealed no evidence of malignancy. Given the patient's previous cancer history and the occurrence of cancer in close relatives, genetic testing of peripheral blood was performed, which revealed the diagnosis of Lynch syndrome. Furthermore, the variant responsible for Lynch syndrome was found to be a mutation of NM_000251.3:c.211 + 1G > C in MSH2.

From organ preservation to selective surgery: How immunotherapy changes colorectal surgery?

The emergence of immunotherapy has revolutionized the traditional treatment paradigm of colorectal cancer (CRC). Among them, immune checkpoint blockade has become the first-line treatment for metastatic colorectal cancer (mCRC) and has made significant progress in the treatment of locally advanced colorectal cancer (LACRC). We reviewed a series of clinical trials that have made breakthrough progress. We will emphasize the breakthrough progress in achieving organ preservation in patients with high microsatellite instability or DNA mismatch repair deficiency (MSI-H/dMMR), and based on this, we propose the concept of selective surgery, which includes selectively removing or preserving lymph nodes, with the aim of proving our idea through more research in the future.

Outcome of Patients With Early-Stage Mismatch Repair Deficient Colorectal Cancer Receiving Neoadjuvant Immunotherapy: A Systematic Review

PURPOSE

We conducted a systematic review to evaluate the outcome of patients with early-stage (stages I-III) mismatch repair deficient (dMMR) colorectal cancer (CRC) receiving neoadjuvant immunotherapy (NIT) with immune checkpoint inhibitor (ICI)-based regimens.

METHODS

MEDLINE, Scopus, Embase, Web of Science, and Cochrane Central Register of Controlled Trials were searched for publications reporting the outcome of patients with early-stage dMMR CRC receiving NIT. The primary outcome measures were the complete response (CR) rate (clinical CR [cCR] or pathologic CR [pCR]) and the incidence of grade 3 or higher toxicities.

RESULTS

The search identified 37 publications that included 423 patients with colon (n = 326, 77%) and rectal (n = 97,23%) cancers aged 19-82 years; most patients had stage III CRC (88%). Approximately 67% of patients received monotherapy with anti-PD-1 agents; the rest received dual ICIs (ipilimumab plus nivolumab). The CR rate (pCR + cCR) in the overall population was 72% (305 of 423). The R0 resection and pCR rates were 99.3% and 70% among the patients undergoing surgery, respectively. Only four (0.9%) patients had primary resistance to NIT. After median follow-up periods ranging from 4 to 27 months, 3 (0.7%) patients progressed after an initial response. Grade 3 or higher toxicities were uncommon (6.3%), rarely delaying planned surgery.

CONCLUSION

NIT in patients with early-stage dMMR CRC is associated with a high response rate, low primary resistance to immunotherapy and cancer recurrence rate, and an excellent safety profile. The findings of the present systematic review support further investigation of NIT in patients with early-stage dMMR CRC, with a particular emphasis on the organ-preserving potential of this strategy.

Neoadjuvant immunotherapy for dMMR/MSI-H locally advanced rectal cancer: The future new standard approach?

INTRODUCTION

This is a review of the evidence from studies of the efficacy and tolerability of neoadjuvant immunotherapy for mismatch repair-deficient (dMMR) or microsatellite instability-high (MSI-H) Locally Advanced Rectal Cancer (LARC).

METHODS

For this review, we searched EMBASE and MEDLINE until 22 September 2022. The terms used in the search included mismatch repair-deficient, microsatellite instability, rectal cancer, neoadjuvant and immunotherapy.

RESULTS

A total of 92 studies were obtained but only 9 were selected for the final analysis (one prospective and eight retrospective studies), including less than 20 patients per study. Neoadjuvant immunotherapy provides overall response rates of 100% (with and completed clinical response between 40 and 100%).

CONCLUSION

Our review discusses completed prospective and retrospective studies, ongoing clinical trials, and the clinical practice of using neoadjuvant immunotherapy for MSI-H/dMMR LARC. The promising results obtained, would open the door to exploring other alternatives for these patients, offering the possibility of avoiding chemoradiation therapy and surgery in the future.

Meta-analysis of neoadjuvant immunotherapy for non-metastatic colorectal cancer

Background

Immunotherapy has been approved for the treatment of metastatic colorectal cancer. The efficacy and safety of neoadjuvant immunotherapy for the treatment of non-metastatic colorectal cancer remains unclear. We tried to explore clinical effect of neoadjuvant immunotherapy in the treatment of non-metastatic colorectal cancer.

Methods

We searched the databases (PubMed, Wanfang Embase, Cochrane Library and China National Knowledge Infrastructure databases) to obtain suitable articles up to September 2022. The primary outcomes of pathological complete response (pCRs), major pathological response (MPR), objective response rate (ORR), R0-resection and anus preserving rate were collected and evaluated. Secordary outcomes (pCRs and MPR) of subgroup analysis between deficient mismatch repair/microsatellite instability-high group (dMMR/MSI-H) and proficient mismatch repair/microsatellite stable group (pMMR/MSS) and outcomes for rectal cancer were analyzed for the final results.

Results

We included ten articles and 410 cases of non-metastatic colorectal cancer with neoadjuvant immunotherapy. There were 113 (27.5%) cases with the dMMR/MSI-H status and 167 (40.7%) cases with the pMMR/MSS status. pCRs was found in 167/373 (44.6%) patients (ES: 0.49, 95% CI: 0.36 to 0.62, P<0.01, chi² = 65.3, P<0.01, I ² = 86.2%) and MPR was found in 194/304 (63.8%) patients (ES: 0.66, 95% CI: 0.54 to 0.78, P<0.01, chi² = 42.55, P<0.01, I ² = 81.2%) with the random-effects model and huge heterogeneity. In the subgroup analysis, pCRs was higher in the dMMR/MSI-H group than the pMMR/MSS group in the fixed-effects model with minimal heterogeneity (OR: 3.55, 95% CI: 1.74 to 7.27, P<0.01, chi² = 1.86, P=0.6, I ² = 0%). pCRs was found in 58/172 (33.9%) rectal cancer patients (ES: 0.33, 95% CI: 0.26 to 0.40, P<0.01, chi² = 3.04, P=0.55, I ² = 0%) with the fixed-effects model and little heterogeneity.

Conclusion

Neoadjuvant immunotherapy could increase pCRs and MPR rate for non-metastatic colorectal cancer. Neoadjuvant immunotherapy could achieve better pCRs rate in dMMR/MSI-H group than in the pMMR/MSS group. Neoadjuvant immunotherapy could be another treatment option for non-metastatic colorectal cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#myprospero, identifier CRD42022350523.

Preoperative Prediction of Microsatellite Instability in Rectal Cancer Using Five Machine Learning Algorithms Based on Multiparametric MRI Radiomics

Objectives: To establish and verify radiomics models based on multiparametric MRI for preoperatively identifying the microsatellite instability (MSI) status of rectal cancer (RC) by comparing different machine learning algorithms. Methods: This retrospective study enrolled 383 (training set, 268; test set, 115) RC patients between January 2017 and June 2022. A total of 4148 radiomics features were extracted from multiparametric MRI, including T₂-weighted imaging, T₁-weighted imaging, apparent diffusion coefficient, and contrast-enhanced T₁-weighted imaging. The analysis of variance, correlation test, univariate logistic analysis, and a gradient-boosting decision tree were used for the dimension reduction. Logistic regression, Bayes, support vector machine (SVM), K-nearest neighbor (KNN), and tree machine learning algorithms were used to build different radiomics models. The relative standard deviation (RSD) and bootstrap method were used to quantify the stability of these five algorithms. Then, predictive performances of different models were assessed using area under curves (AUCs). The performance of the best radiomics model was evaluated using calibration and discrimination. Results: Among these 383 patients, the prevalence of MSI was 14.62% (56/383). The RSD value of logistic regression algorithm was the lowest (4.64%), followed by Bayes (5.44%) and KNN (5.45%), which was significantly better than that of SVM (19.11%) and tree (11.94%) algorithms. The radiomics model based on logistic regression algorithm performed best, with AUCs of 0.827 and 0.739 in the training and test sets, respectively. Conclusions: We developed a radiomics model based on the logistic regression algorithm, which could potentially be used to facilitate the individualized prediction of MSI status in RC patients.

Updates in gynecologic care for individuals with lynch syndrome

Lynch syndrome is an autosomal dominant hereditary cancer syndrome caused by germline pathogenic variants (PVs) in DNA mismatch repair genes (MLH1, MSH2, PMS2, MSH6) or the EPCAM gene. It is estimated to affect 1 in 300 individuals and confers a lifetime risk of cancer of 10-90%, depending on the specific variant and type of cancer. Lynch syndrome is the most common cause of inherited colorectal cancer, but for women, endometrial cancer is more likely to be the sentinel cancer. There is also evidence that certain PVs causing Lynch syndrome confer an increased risk of ovarian cancer, while the risk of ovarian cancer in others is not well defined. Given this, it is essential for the practicing gynecologist and gynecologic oncologist to remain up to date on the latest techniques in identification and diagnosis of individuals with Lynch syndrome as well as evidence-based screening and risk reduction recommendations for those impacted. Furthermore, as the landscape of gynecologic cancer treatment shifts towards treatment based on molecular classification of tumors, knowledge of targeted therapies well-suited for mismatch repair deficient Lynch tumors will be crucial. The objective of this review is to highlight recent updates in the literature regarding identification and management of individuals with Lynch syndrome as it pertains to endometrial and ovarian cancers to allow gynecologic providers the opportunity to both prevent and identify Lynch-associated cancers earlier, thereby reducing the morbidity and mortality of the syndrome.

Pathological Complete Response Following Neoadjuvant Tislelizumab Monotherapy in Treatment-Naive Locally Advanced, MMR-Deficient/MSI-High Ascending Colon Cancer: A Case Report

Although recent trials started the use of neoadjuvant immunotherapy (NIT) in instability-high (MSI-H) or mismatch repair deficient (dMMR) early-stage or locally advanced colorectal cancer (LACRC), little data on the treatment strategy of NIT has been shown, and whether the tirelizumab mono-immune checkpoint inhibitor (ICI) can be used as NIT for patients with LACRC has not been reported as yet. In this study we report on a locally advanced ascending colon cancer case with a history of incomplete intestinal obstruction which achieved a pathologic complete response (pCR) after treated with Tirelizumab as NIT. A 32-year-old man was diagnosed with locally advanced ascending colon cancer with MSI-H and dMMR. An incomplete intestinal obstruction accompanied with hyperpyrexia occurred unexpectedly and was eased by symptomatic treatment. There was no peritonitis or other acute complications. NIT (three cycles of Tirelizumab) was suggested by the MDT board and partial response was achieved according to CT scanning, and pCR was further revealed by postoperative pathology. A ctDNA clearance confirmed the R0 resection and some immunotherapy related predictors were also detected using the NGS method. Our case study contributes to the evidence on the feasibility, efficacy, and safety of f Tirelizumab as a mono ICI for an optional neoadjuvant therapy in patients with MSI-H/dMMR LACRC.

Pathologic complete response after laparoscopic surgery following treatment with nivolumab and ipilimumab for anticancer drug-resistant MSI-high descending colon cancer: a case report and literature review

BACKGROUND

Preoperative treatment is performed for locally advanced colon cancer with extensive tumor proximity or suspected invasion of skeletal muscles, major organs, and blood vessels. Oxaliplatin-based regimens are often used in preoperative chemotherapy. However, microsatellite instability (MSI)-high colorectal cancer is often resistant to cytotoxic anticancer agents. Herein, we describe a case of treatment of anticancer drug-resistant MSI-high locally advanced colon cancer and review cases of complete response to immune checkpoint inhibitor therapy for colorectal cancer.

CASE PRESENTATION

A 57-year-old woman was referred to our hospital with a large tumor in the descending colon and extensive thoracic and abdominal wall involvement, including the ribs and diaphragm. No distant metastasis was observed. The tumor had perforated the abdominal wall and formed an abscess. Upon visiting our hospital, emergency surgery was performed. An abdominal wall incision was made to drain the abscess and laparoscopic colostomy was performed. Histopathological examination of biopsy specimens revealed an adenocarcinoma with positive immunohistochemical expressions of both CDX2 and CK20. The patient was diagnosed with a descending colon cancer. Genetic examination found MSI-high, Kras mutation (F12G), and wild-type BRAF. After the inflammation improved, chemotherapy with the FOLFIRI regimen was initiated, but the tumor grew rapidly. As a second-line treatment, nivolumab and ipilimumab combination therapy was initiated. After four cycles of these therapies, the patient was administered nivolumab alone for five cycles. Tumor shrinkage was observed and radical surgery was performed. The patient underwent laparoscopic descending colon and partial thoracic and abdominal wall resection. The abdominal wall muscle was dissected from the abdominal cavity, and subcutaneous tissues, diaphragm, ribs were dissected from the body surface. Pathological examination revealed mucus components, fibrous tissues, and no malignant cells, indicating a complete pathological response (pCR). The patient had a good postoperative course and returned to work after being discharged. No recurrence was observed six months postoperatively.

CONCLUSIONS

Herein, we report a case of anticancer drug-resistant MSI-high colon cancer that was resected after treatment with immune checkpoint inhibitors, and a pCR was achieved. This new treatment strategy can be used for the treatment of cases that are not responsive to conventional therapies.

Pathological complete response after neoadjuvant immunotherapy combined with chemotherapy in pediatric rectal carcinoma: A case report

Background

Pediatric colorectal carcinoma (PCRC) is a rare non-embryonal tumor with an incidence of 0.1% to 1% of adults. Immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) have shown significant efficacy in defective mismatch repair/Microsatellite instability-high (dMMR/MSI-H) metastatic CRC (mCRC). Although several studies have reported neoadjuvant immunotherapy (NIT) in MSI-H/dMMR non-mCRC patients, not all patients achieved pathological complete remission (pCR). There are differences between PCRC and adult colorectal carcinoma (CRC), and the role of NIT in PCRC remains to be further defined.

Case presentation

We report the case of a 12-year-old child who was admitted to the hospital with abdominal pain and vomiting for more than 3 months. The child's diagnosis was difficult and complex. He was initially diagnosed with intestinal obstruction, eventually diagnosed with a rare PCRC and identified as locally advanced colorectal cancer (LACRC) with genetic sequencing results showing MSI-H. After a thorough evaluation by clinicians, he received 4 cycles of Camrelizumab (anti-PD-1 antibody) + CapeOx (capecitabine and oxaliplatin) NIT combination chemotherapy. Repeat imaging and all tumor markers were unremarkable, and R0 resection was achieved. Postoperative pathology showed a tumor regression grade (TRG) of 0 grade determined as pCR. Postoperative review has not shown any recurrence or metastasis to date and the prognosis is good.

Conclusion

PCRC should improve the diagnostic efficiency to prevent misdiagnosis and miss the best time for treatment. NIT and or chemotherapy can be a reasonable and effective treatment option for dMMR/MSI-H locally advanced PCRC. Our report provides some support and evidence for neoadjuvant immunotherapy for locally advanced PCRC, while highlighting the importance of preoperative detection of microsatellite status for locally advanced PCRC.

A Tumoral and Peritumoral CT-Based Radiomics and Machine Learning Approach to Predict the Microsatellite Instability of Rectal Carcinoma

Objective

To predict the status of microsatellite instability (MSI) of rectal carcinoma (RC) using different machine learning algorithms based on tumoral and peritumoral radiomics combined with clinicopathological characteristics.

Methods

There were 497 RC patients enrolled in this retrospective study. The tumoral and peritumoral CT-based radiomic features were calculated after tumor segmentation. The radiomic features from two radiologists were compared by way of inter-observer correlation coefficient (ICC). After methods of variance, correlation, and dimension reduction, six machine learning algorithms of logistic regression (LR), Bayes, support vector machine, random forest, k-nearest neighbor, and decision tree were conducted to develop models for predicting MSI status of RC. The relative standard deviation (RSD) was quantified. The radiomics and significant clinicopathological variables constituted the radiomics-clinicopathological nomogram. The receiver operator curve (ROC) was made by DeLong test, and the area under curve (AUC) with 95% confidence interval (95% CI) was calculated to evaluate the performance of the model.

Results

The venous phase of CT examination was selected for further analysis because the proportion of radiomic features with ICC greater than 0.75 was higher. The tumoral and peritumoral model by LR algorithm (M-LR) with minimal RSD showed good performance in predicting MSI status of RC with the AUCs of 0.817 and 0.726 in the training and validation set. The radiomic-clinicopathological nomogram performed better in both the training and validation set with AUCs of 0.843 and 0.737.

Conclusion

The radiomics-clinicopathological nomogram demonstrated better predictive performance in evaluating the MSI status of RC.

Predicting Mismatch-Repair Status in Rectal Cancer Using Multiparametric MRI-Based Radiomics Models: A Preliminary Study

Detecting mismatch-repair (MMR) status is crucial for personalized treatment strategies and prognosis in rectal cancer (RC). A preoperative, noninvasive, and cost-efficient predictive tool for MMR is critically needed. Therefore, this study developed and validated machine learning radiomics models for predicting MMR status in patients directly on preoperative MRI scans. Pathologically confirmed RC cases administered surgical resection in two distinct hospitals were examined in this retrospective trial. Totally, 78 and 33 cases were included in the training and test sets, respectively. Then, 65 cases were enrolled as an external validation set. Radiomics features were obtained from preoperative rectal MR images comprising T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI), and combined multisequences. Four optimal features related to MMR status were selected by the least absolute shrinkage and selection operator (LASSO) method. Support vector machine (SVM) learning was adopted to establish four predictive models, i.e., Model_T2WI, Model_DWI, Model_CE-T1WI, and Model_combination, whose diagnostic performances were determined and compared by receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Model_combination had better diagnostic performance compared with the other models in all datasets (all p < 0.05). The usefulness of the proposed model was confirmed by DCA. Therefore, the present pilot study showed the radiomics model combining multiple sequences derived from preoperative MRI is effective in predicting MMR status in RC cases.

DNA Mismatch Repair-deficient Rectal Cancer Is Frequently Associated With Lynch Syndrome and With Poor Response to Neoadjuvant Therapy

We evaluated 368 consecutively resected rectal cancers with neoadjuvant therapy for DNA mismatch repair (MMR) protein status, tumor response to neoadjuvant therapy, histopathologic features, and patient survival. Nine (2.4%) rectal cancers were mismatch repair-deficient (MMRD): 8 (89%) Lynch syndrome-associated tumors and 1 (11%) sporadic MLH1-deficient tumor. Of the 9 MMRD rectal cancers, 89% (8/9) had a tumor regression score 3 (poor response) compared with 23% (81/359) of MMR proficient rectal cancers (P<0.001). Patients with MMRD rectal cancer less often had downstaging after neoadjuvant therapy compared with patients with MMR proficient rectal cancer (11% vs. 57%, P=0.007). In the multivariable logistic regression analysis, MMRD in rectal cancer was associated with a 25.11-fold increased risk of poor response to neoadjuvant therapy (tumor regression score 3) (95% confidence interval [CI]: 3.08-44.63, P=0.003). In the multivariable Cox regression analysis, the only variables significantly associated with disease-free survival were pathologic stage III disease (hazard ratio [HR]=2.46, 95% CI: 1.54-3.93, P<0.001), College of American Pathologists (CAP) tumor regression score 2 to 3 (HR=3.44, 95% CI: 1.76-6.73, P<0.001), and positive margins (HR=2.86, 95% CI: 1.56-5.25, P=0.001). In conclusion, we demonstrated that MMRD in rectal cancer is an independent predictor of poor response to neoadjuvant therapy and infrequently results in pathologic downstaging following neoadjuvant therapy. We also confirmed that MMRD in rectal cancer is strongly associated with a diagnosis of Lynch syndrome. Our results suggest that MMR status may help to provide a more patient-centered approach when selecting neoadjuvant treatment regimens and may help predict tumor response to neoadjuvant therapy.

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.