and fusions are targetable mutations that occur in a subset of patients with non-small cell lung cancer (NSCLC). and have been understood to be independent oncogenic drivers which do not co-occur with other common tyr...and fusions are targetable mutations that occur in a subset of patients with non-small cell lung cancer (NSCLC). and have been understood to be independent oncogenic drivers which do not co-occur with other common tyrosine kinase receptor mutations except in the acquired resistance setting. Here we present a case of a patient with stage IV fusion NSCLC discovered initially with RNA next generation sequencing (NGS) who acquired resistance to lorlatinib after 6 months on therapy through a novel fusion, detected only through RNA NGS. Combination therapy targeting RET and ROS1 using pralsetinib and lorlatinib achieved a partial response with limited durability of only four months. This is the first reported case of a fusion as a potential mechanism of resistance to lorlatinib, it identifies a novel fusion partner, and it emphasizes the importance of testing for acquired resistance mutations with both DNA and RNA at the time of progression in patients with targetable oncogenic drivers.
Lopes MA, Cordeiro MER, de Alencar Teles Barreto F
… +6 more, de Souza Moreno L, de Medeiros Silva AA, de Loyola MB, Soares MVA, de Sousa JB, Pittella-Silva F
Approximately two-thirds of patients with colorectal cancer (CRC) undergo resection with curative intent; however, 30% to 50% of these patients experience recurrence. The concentration of cell-free DNA (cfDNA) before and...Approximately two-thirds of patients with colorectal cancer (CRC) undergo resection with curative intent; however, 30% to 50% of these patients experience recurrence. The concentration of cell-free DNA (cfDNA) before and after surgery may be related to the prognosis of patients with CRC, but there is limited information regarding cfDNA levels at the time of surgery. Here, we analyzed surgical cfDNA release using plasma samples from 30 colorectal cancer patients at three key points during surgery: preoperative (immediately before surgery), intraoperative (during surgery), and postoperative (at the end of surgery). Automated electrophoresis was used to analyze cfDNA concentrations and fragment sizes, which were then correlated with clinical variables. Our findings indicate a significant increase in cfDNA release during and after surgery (2.8- and 2.2-fold higher respectively, < 0.01). Characteristic fragments of cfDNA (<400 bp) predominated at all surgical stages; however, the release of genomic material (>400 bp) was also observed. We found that cfDNA concentration increases during and after surgery in patients over 60 years old (2.9-fold higher intraoperatively than preoperatively and 2.3 folds higher postoperatively than preoperatively, < 0.01); in patients with comorbidities (3.0-fold higher intraoperatively and 2.3-fold higher postoperatively, < 0.01); and in patients with CEA levels >5 ng/mL (3.1-fold higher intraoperatively and 1.3-fold higher postoperatively, < 0.01). Interestingly, cfDNA release during surgery is significantly higher in patients with adverse clinical characteristics. Patients bearing locally advanced tumors or metastasis had a 3.1-fold increase in cfDNA release intraoperatively and 2.4-fold increase postoperatively, < 0.01. cfDNA concentration also increases intraoperatively in patients with a high score of tumor buds (2.6 folds higher, < 0.02), patients with perineural invasion (3.4-fold higher, < 0.02) and in patients with lymphovascular invasion (3.1-fold higher, < 0.05). Furthermore, we observed that cfDNA concentration may rise in correlation with the duration of the surgery, highlighting its potential as a marker of surgical quality. Taken together, our results suggest that in addition to physiological age, comorbidities and unfavorable clinical traits, intense surgical manipulation from the tumor's extent, may result in greater tissue damage and elevated cfDNA release.
Recently, combination checkpoint therapy of cancer has been recognized as producing additive as opposed to synergistic benefit due in part to positively correlated effects. The potential for uncorrelated or negatively co...Recently, combination checkpoint therapy of cancer has been recognized as producing additive as opposed to synergistic benefit due in part to positively correlated effects. The potential for uncorrelated or negatively correlated therapies to produce true synergistic benefits has been noted. Whereas the inhibitory receptors PD-1, CTLA-4, TIM-3, LAG-3, and TIGIT have been collectively characterized as exhaustion receptors, another inhibitory receptor KLRG1 was historically characterized as a senescent receptor and received relatively little attention as a potential checkpoint inhibitor target. The anti-tumor effects of KLRG1 blockade has relatively recently been demonstrated in preclinical studies. Here, expression of the inhibitory receptors PD-1, CTLA-4, TIM-3, LAG-3, TIGIT, and KLRG1 was studied in publicly available gene expression datasets. Bulk RNA microarray and RNAseq, and single cell RNAseq data from healthy blood and tumor tissue samples were analyzed for Pearson correlation. CD8 T cell differentiation of memory T cells from the TEM to TEMRA states is characterized by PD-1/KLRG1 anti-correlation, with decreased PD-1 expression but increased KLRG1 expression. Single cell RNAseq analysis of tumor infiltrating CD8 T cells shows positive correlation of CTLA-4, TIM-3, LAG-3, TIGIT, GITR, 4-1BB, and OX40 with PD-1 but negative correlation of KLRG1 with PD-1. The anti-correlation of PD-1 and KLRG1 expression in human tumor infiltrating CD8 T cells suggests the potential for combination therapy supra-additive benefits of anti-PD-1 and anti-KLRG1 therapies.
The FDA approval on September 29, 2023, for "class III " blood tests to assess hereditary cancer risk make widely available tests that may be obtained through a Direct to Consumer (DTC) path. There is concern that germ-l...The FDA approval on September 29, 2023, for "class III " blood tests to assess hereditary cancer risk make widely available tests that may be obtained through a Direct to Consumer (DTC) path. There is concern that germ-line predisposition tests may not be reimbursed by insurance adding financial burdens to individuals and families. It is generally agreed in the fields of oncology and genetics that germ-line testing for disease susceptibility including cancer is best performed under care of a healthcare provider with genetic counseling. Our recommended cautions and call for change may seem paternalistic to some and may appear to infringe upon constitutional rights as they may relate to DTC, but there is a real concern with harm from germ-line testing of both adults and minors that can occur through DTC tests. The DTC option of germ-line testing for cancer susceptibility should be discouraged given the risks of anxiety, lack of adequate interpretation for variants not strongly associated with cancer, potential for minors to be tested outside the healthcare system and potential for loss of follow-up if test results are not shared with health care professionals or never make it into the medical record. The FDA should consider clear unambiguous guidance when it comes to germ-line DTC testing for cancer susceptibility for adults and especially for minors.
Primary sclerosing cholangitis (PSC) is a chronic liver disease characterized by inflammation and scarring of the bile ducts, which can lead to cirrhosis and hepatic decompensation. The study aimed to explore the potenti...Primary sclerosing cholangitis (PSC) is a chronic liver disease characterized by inflammation and scarring of the bile ducts, which can lead to cirrhosis and hepatic decompensation. The study aimed to explore the potential value of computational radiomics, a field that extracts quantitative features from medical images, in predicting whether or not PSC patients had hepatic decompensation. We used an in-house developed deep learning model called the body composition model, which quantifies body composition from computed tomography (CT) into four compartments: subcutaneous adipose tissue (SAT), skeletal muscle (SKM), visceral adipose tissue (VAT), and intermuscular adipose tissue (IMAT). We extracted radiomics features from all four body composition compartments and used them to build a predictive model in the training cohort. The predictive model demonstrated good performance in validation cohorts for predicting hepatic decompensation, with an accuracy score of 0.97, a precision score of 1.0, and an area under the curve (AUC) score of 0.97. Computational radiomics using CT images shows promise in predicting hepatic decompensation in primary sclerosing cholangitis patients. Our model achieved high accuracy, but predicting future events remains challenging. Further research is needed to validate clinical utility and limitations.
Mesenchymal stem cells (MSCs) are recognized for their immunomodulatory capabilities, tumor-homing abilities, and capacity to serve as carriers for therapeutic agents. This review delves into the role of adoptively trans...Mesenchymal stem cells (MSCs) are recognized for their immunomodulatory capabilities, tumor-homing abilities, and capacity to serve as carriers for therapeutic agents. This review delves into the role of adoptively transferred MSCs in tumor progression, their interactions with the tumor microenvironment, and their use in delivering anti-cancer drugs, oncolytic viruses, and genetic material. It also addresses the challenges and limitations associated with MSC therapy, such as variability in MSC preparations and potential tumorigenic effects emphasizing the need for advanced genetic engineering and personalized approaches to enhance therapeutic efficacy. The review concludes with an optimistic outlook on the future of MSC-based therapies, underscoring their promise to develop effective and personalized cancer treatments.
Persistence images, derived from topological data analysis, emerge as a powerful tool for visualizing and mitigating biases in radiological data interpretation and AI model development. This technique transforms complex...Persistence images, derived from topological data analysis, emerge as a powerful tool for visualizing and mitigating biases in radiological data interpretation and AI model development. This technique transforms complex topological features into stable, interpretable representations, offering unique insights into medical imaging data structure. By providing intuitive visualizations, persistence images enable the identification of subtle structural differences and potential biases in data acquisition, interpretation, and AI model training. Persistence images can also facilitate stratified sampling, matching statistics, and noise filtration, enhancing the accuracy and equity of radiological analysis. Despite challenges in computational complexity and workflow integration, persistence images show promise in developing more accurate, equitable, and trustworthy AI systems in radiology, potentially improving patient outcomes and personalized healthcare delivery.
Persistence barcodes emerge as a promising tool in radiological analysis, offering a novel approach to reduce bias and uncover hidden patterns in medical imaging. By leveraging topological data analysis, this technique p...Persistence barcodes emerge as a promising tool in radiological analysis, offering a novel approach to reduce bias and uncover hidden patterns in medical imaging. By leveraging topological data analysis, this technique provides a robust, multi-scale perspective on image features, potentially overcoming limitations in traditional methods and Graph Neural Networks. While challenges in interpretation and implementation remain, persistence barcodes show significant potential for improving diagnostic accuracy, standardization, and ultimately, patient outcomes in the evolving field of radiology.
Persistence landscapes, a sophisticated tool from topological data analysis, offer a promising approach to address biases in radiological interpretation and AI model development. By transforming complex topological featu...Persistence landscapes, a sophisticated tool from topological data analysis, offer a promising approach to address biases in radiological interpretation and AI model development. By transforming complex topological features into statistically analyzable functions, they enable robust comparisons between populations and datasets. Persistence landscapes excel in noise filtration, fusion bias mitigation, and enhancing machine learning models. Despite challenges in computation and integration, they show potential to improve the accuracy and equity of radiological analysis, particularly in multi-modal imaging and AI-assisted interpretation.
Topological Data Analysis (TDA) and simplicial complexes offer a novel approach to address biases in AI-assisted radiology. By capturing complex structures, n-way interactions, and geometric relationships in medical imag...Topological Data Analysis (TDA) and simplicial complexes offer a novel approach to address biases in AI-assisted radiology. By capturing complex structures, n-way interactions, and geometric relationships in medical images, TDA enhances feature extraction, improves representation robustness, and increases interpretability. This mathematical framework has the potential to significantly improve the accuracy and fairness of radiological assessments, paving the way for more equitable patient care.
Modern cancer management comprises a variety of treatment strategies. Immunotherapy, while successful at treating many cancer subtypes, is often hindered by tumor immune evasion and T cell exhaustion as a result of an im...Modern cancer management comprises a variety of treatment strategies. Immunotherapy, while successful at treating many cancer subtypes, is often hindered by tumor immune evasion and T cell exhaustion as a result of an immunosuppressive tumor microenvironment (TME). In solid malignancies, the extracellular matrix (ECM) embedded within the TME plays a central role in T cell recognition and cancer growth by providing structural support and regulating cell behavior. Relative to healthy tissues, tumor associated ECM signatures include increased fiber density and alignment. These and other differentiating features contributed to variation in clinically observed tumor-specific ECM configurations, collectively referred to as Tumor-Associated Collagen Signatures (TACS) 1-3. TACS is associated with disease progression and immune evasion. This review explores our current understanding of how ECM geometry influences the behaviors of both immune cells and tumor cells, which in turn impacts treatment efficacy and cancer evolutionary progression. We discuss the effects of ECM remodeling on cancer cells and T cell behavior and review recent models of cancer-immune interactions.
Cheng D, Zhao S, Tang H
… +16 more, Zhang D, Sun H, Yu F, Jiang W, Yue B, Wang J, Zhang M, Yu Y, Liu X, Sun X, Zhou Z, Qin X, Zhang X, Yan D, Wen Y, Peng Z