Biomarkers and cell-based models to predict the outcome of neoadjuvant therapy for rectal cancer patients

Predictive Value of the Interaction between CEA and Hemoglobin in Neoadjuvant CCRT Outcomes in Rectal Cancer Patients

The adoption of neoadjuvant concurrent chemoradiotherapy (CCRT) has reshaped the therapeutic landscape, but response prediction remains challenging. This study investigates the interaction between pre-CCRT carcinoembryonic antigen (CEA) and post-CCRT hemoglobin (Hb) levels in predicting the response of locally advanced rectal cancer (LARC) to CCRT. Retrospective data from 93 rectal cancer patients receiving neoadjuvant CCRT were analyzed. Univariate analyses assessed clinical factors associated with tumor regression grade (TRG) and T-stage outcomes. Machine learning identified predictive biomarkers. Interaction effects between CEA and Hb were explored through subgroup analyses. Post-CCRT Hb varied between pre-CCRT CEA groups. The interaction between pre-CCRT CEA and post-CCRT Hb influenced TRG. Males with normal pre-CCRT CEA and anemia showed better treatment responses. Females with elevated pre-CCRT CEA and post-CCRT anemia exhibited poorer responses. The interaction effect between them was significant, indicating that their relationship with TRG was not additive. Inflammatory biomarkers, WBC, neutrophil count, and post-CCRT platelet level correlated with CCRT response. Contrasting with previous findings, anemia was a predictor of better treatment response in males with normal pre-CCRT CEA. The interaction between pre-CCRT CEA and post-CCRT Hb levels predicts the response of LARC to CCRT. CEA, Hb, and sex should be considered when assessing treatment response. Inflammatory biomarkers contribute to response prediction. Understanding these complex relationships can enhance personalized treatment approaches in rectal cancer patients.

Predictive markers for anti-inflammatory treatment response in thyroid eye disease

Anti-inflammatory treatment is the primary and vital therapeutic approach for active, moderate-to-severe thyroid eye disease (TED). Accurate pretreatment prediction of treatment response is of paramount importance for the prognosis of patients. However, relying solely on the clinical activity score asa determinant of activity has led to unsatisfactory treatment outcomes. In recent years, significant advancements have been made in identifying predictive markers for anti-inflammatory treatment response in TED, clinical markers, body fluid biomarkers and imaging biomarkers. Several clinical studies have developed prediction models based on these markers. However, there is still a lack of comprehensive elucidation or comparison between the different markers. Therefore, this review aims to provide a detailed analysis of the definition, characteristics, and application of predictive markers for anti-inflammatory treatment response in TED. Through detailed literature search, 26 articles applying anti-inflammatory treatment effect prediction with a total of 1948 TED patients were used for analysis and discussion. By gaining a better understanding of the current research on predictive markers, we can accelerate and guide the exploration of treatment prediction strategies, leading us towards an era of precise therapy for TED.

Multiphase and multiparameter MRI-based radiomics for prediction of tumor response to neoadjuvant therapy in locally advanced rectal cancer

BACKGROUND

To develop and validate radiomics models for prediction of tumor response to neoadjuvant therapy (NAT) in patients with locally advanced rectal cancer (LARC) using both pre-NAT and post-NAT multiparameter magnetic resonance imaging (mpMRI).

METHODS

In this multicenter study, a total of 563 patients were included from two independent centers. 453 patients from center 1 were split into training and testing cohorts, the remaining 110 from center 2 served as an external validation cohort. Pre-NAT and post-NAT mpMRI was collected for feature extraction. The radiomics models were constructed using machine learning from a training cohort. The accuracy of the models was verified in a testing cohort and an independent external validation cohort. Model performance was evaluated using area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

The model constructed with pre-NAT mpMRI had favorable accuracy for prediction of non-response to NAT in the training cohort (AUC = 0.84), testing cohort (AUC = 0.81), and external validation cohort (AUC = 0.79). The model constructed with both pre-NAT and post-NAT mpMRI had powerful diagnostic value for pathologic complete response in the training cohort (AUC = 0.86), testing cohort (AUC = 0.87), and external validation cohort (AUC = 0.87).

CONCLUSIONS

Models constructed with multiphase and multiparameter MRI were able to predict tumor response to NAT with high accuracy and robustness, which may assist in individualized management of LARC.

IMMUNOREACT 0: Biopsy-based immune biomarkers as predictors of response to neoadjuvant therapy for rectal cancer-A systematic review and meta-analysis

BACKGROUND

The main therapy for rectal cancer patients is neoadjuvant therapy (NT) followed by surgery. Immune biomarkers are emerging as potential predictors of the response to NT. We performed a meta-analysis to estimate their predictive significance.

METHODS

A systematic literature search of PubMed, Ovid MEDLINE and EMBASE databases was performed to identify eligible studies. Studies on patients with rectal cancer undergoing NT in which the predictive significance of at least one of the immunological markers of interest was assessed by immunohistochemistry (IHC) in pretreatment biopsies were included.

RESULTS

Seventeen studies reporting sufficient data met the inclusion criteria for meta-analysis. High levels of total CD3+, CD4+ and CD8+ tumor infiltrating lymphocytes (TILs), as well as stromal and intraepithelial CD8+ compartments, significantly predicted good pathological response to NT. Moreover, high levels of total (tumoral and immune cell expression) PD-L1 resulted associated to a good pathological response. On the contrary, high levels of intraepithelial CD4+ TILs were correlated with poor pathological response. FoxP3+ TILs, tumoral PD-L1 and CTLA-4 were not correlated to the treatment response.

CONCLUSION

This meta-analysis indicated that high-density TILs might be predictive biomarkers of pathological response in patients that underwent NT for rectal cancer.

Predictive biomarkers in radioresistant rectal cancer: a systematic review

BACKGROUND AND AIMS

The treatment of locally advanced rectal cancer often consists of neoadjuvant chemoradiotherapy followed by surgery. However, approximately 15% of patients show no response to this neoadjuvant chemoradiotherapy. This systematic review aimed to identify biomarkers of innate radioresistant rectal cancer.

METHOD

Through a systematic literature search, 125 papers were included and analyzed using ROBINS-I, a Cochrane risk of bias tool for non-randomized studies of interventions. Both statistically significant and nonsignificant biomarkers were identified. Biomarkers mentioned more than once in the results or biomarkers with a low or moderate risk of bias were included as the final results.

RESULTS

Thirteen unique biomarkers, three genetic signatures, one specific pathway, and two combinations of two or four biomarkers were identified. In particular, the connection between HMGCS2, COASY, and PI3K-pathway seems promising. Future scientific research should focus on further validating these genetic resistance markers.

Multimodal Treatment of Rectal Cancer

BACKGROUND

Colorectal cancer is one of the three most common types of cancer in Germany. Approximately 30% of these cancers are located in the rectum, corresponding to about 18 000 new cases per year.

METHODS

This review is based on publications retrieved by a selective search in the PubMed database, including current guidelines and recommendations.

RESULTS

Specialized imaging, particularly magnetic resonance imaging, is essential for treatment planning. In very early stages of this disease, tumors without risk factors can be excised locally. Otherwise, radical surgical resection with lymphadenectomy remains the standard treatment, and can be performed either minimally invasive or open. At present, neoadjuvant treatment plans are evolving in the direction of total neoadjuvant therapy. In addition, recent studies investigate whether the improved efficacy of neoadjuvant therapy might now enable patients with a complete clinical remission to be spared from surgical resection (organ-preserving watch-and-wait strategy).

CONCLUSION

The treatment of rectal cancer is a prime example of an interdisciplinary, multimodal approach. In the past, the focus was mainly on improving oncologic outcomes; at present, increasing attention is being devoted to the patients' quality of life as well and the functional aspects of the various modes of treatment.

Patient-derived rectal cancer organoids—applications in basic and translational cancer research

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and among the leading causes of death in both men and women. Rectal cancer (RC) is particularly challenging compared with colon cancer as the treatment after diagnosis of RC is more complex on account of its narrow anatomical location in the pelvis adjacent to the urogenital organs. More and more existing studies have begun to refine the research on RC and colon cancer separately. Early diagnosis and multiple treatment strategies optimize outcomes for individual patients. However, the need for more accurate and precise models to facilitate RC research is underscored due to the heterogeneity of clinical response and morbidity interrelated with radical surgery. Organoids generated from biopsies of patients have developed as powerful models to recapitulate many aspects of their primary tissue, consisting of 3-D self-organizing structures, which shed great light on the applications in both biomedical and clinical research. As the preclinical research models for RC are usually confused with colon cancer, research on patient-derived RC organoid models enable personalized analysis of cancer pathobiology, organizational function, and tumor initiation and progression. In this review, we discuss the various applications of patient-derived RC organoids over the past two years in basic cancer biology and clinical translation, including sequencing analysis, drug screening, precision therapy practice, tumor microenvironment studies, and genetic engineering opportunities.

Tumor organoids: applications in cancer modeling and potentials in precision medicine

Cancer is a top-ranked life-threatening disease with intratumor heterogeneity. Tumor heterogeneity is associated with metastasis, relapse, and therapy resistance. These factors contribute to treatment failure and an unfavorable prognosis. Personalized tumor models faithfully capturing the tumor heterogeneity of individual patients are urgently needed for precision medicine. Advances in stem cell culture have given rise to powerful organoid technology for the generation of in vitro three-dimensional tissues that have been shown to more accurately recapitulate the structures, specific functions, molecular characteristics, genomic alterations, expression profiles, and tumor microenvironment of primary tumors. Tumoroids in vitro serve as an important component of the pipeline for the discovery of potential therapeutic targets and the identification of novel compounds. In this review, we will summarize recent advances in tumoroid cultures as an excellent tool for accurate cancer modeling. Additionally, vascularization and immune microenvironment modeling based on organoid technology will also be described. Furthermore, we will summarize the great potential of tumor organoids in predicting the therapeutic response, investigating resistance-related mechanisms, optimizing treatment strategies, and exploring potential therapies. In addition, the bottlenecks and challenges of current tumoroids will also be discussed in this review.

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.

Discriminating Potential Genetic Markers for Complete Response and Non-Complete Response Patients to Neoadjuvant Chemotherapy with Locally Advanced Rectal Cancer

Background: Neoadjuvant chemoradiotherapy (nCRT) prior to surgery is considered standard therapy for locally advanced rectal cancer. Unfortunately, most patients with rectal cancer are resistant to radiotherapy. This might be a genetic cause. The role of certain rectal cancer-causing genes has not been completely elucidated. This study aims to investigate the genes responsible for locally advanced rectal cancer patients not reacting to radiotherapy. Methods: Whole exome sequencing of the DNA samples was performed on the samples. Bioinformatic analysis on the subjects was established. Individual genetic information was screened to identify differently expressed genes that more frequently appeared in non-complete response (NCR) compared to complete response (CR) patients after nCRT. All variations were verified by Sanger sequencing. Results: Genotyping information and pathway analyses of the samples indicated genes such as FLCN, CALML5, and ANTXR1 to be commonly mutated in CR group, whereas genes such as GALNTL14, CNKSR1, ACD, and CUL3 were more commonly mutated in the NCR group. Chi-square test revealed some significant variants (<0.05) such as rs3744124 (FLCN), rs28365986 (ANTXR1), rs10904516 (CALML5), rs3738952 (CUL3), rs13394 and rs2293013 (PIH1D1), rs2274531 (GPA33), rs4963048 (BRSK2), rs17883366 (IL3RA), rs2297575 (PSMD5), rs2288101 (GALNT14), and rs11954652 (DCTN4). Conclusion: Identifying an array of genes that separate NCRs from CRs would lead to finding genetic biomarkers for early detection of rectal cancer patients that are resistant to nCRT. A further investigation to validate the significance of genetic biomarkers to segregate NCRs from CRs should be performed with a larger CRC dataset. Protein expression levels, as well as transcriptomic analysis, would also help us understand the mechanism of how these genes could play a role in preventing radiation therapy to patients. This would be essential to prevent redundant radiation therapy.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 1: Focus on Immunohistochemical Results with Discussion of Pre-Analytical and Interpretation Variables

Immunotherapy targeting the PD-1-PD-L1 axis yielded good results in treating different immunologically ''hot'' tumors. A phase II study revealed good therapeutic activity of pembrolizumab in selected prostatic carcinoma (PC)-patients. We performed a systematic literature review (PRISMA guidelines), which analyzes the immunohistochemical expression of PD-L1 in human PC samples and highlights the pre-analytical and interpretation variables. Interestingly, 29% acinar PCs, 7% ductal PCs, and 46% neuroendocrine carcinomas/tumors were PD-L1+ on immunohistochemistry. Different scoring methods or cut-off criteria were applied on variable specimen-types, evaluating tumors showing different clinic-pathologic features. The positivity rate of different PD-L1 antibody clones in tumor cells ranged from 3% (SP142) to 50% (ABM4E54), excluding the single case tested for RM-320. The most tested clone was E1L3N, followed by 22C3 (most used for pembrolizumab eligibility), SP263, SP142, and 28-8, which gave the positivity rates of 35%, 11-41% (depending on different scoring systems), 6%, 3%, and 15%, respectively. Other clones were tested in <200 cases. The PD-L1 positivity rate was usually higher in tumors than benign tissues. It was higher in non-tissue microarray specimens (41-50% vs. 15%), as PC cells frequently showed heterogenous or focal PD-L1-staining. PD-L1 was expressed by immune or stromal cells in 12% and 69% cases, respectively. Tumor heterogeneity, inter-institutional preanalytics, and inter-observer interpretation variability may account for result biases.