Recent developments include a novel biomarker that may predict the aggressiveness of pancreatic cancer precursors, insights into the structure and function of a breast and ovarian cancer susceptibility gene, a new approach to overcoming treatment resistance in ovarian cancer, distinguishing features of young-onset rectal cancer, a biomarker and potential target for metastatic lung cancer, machine learning models to better predict outcomes of patients with mantle cell lymphoma (MCL), and a promising therapy for patients with relapsed/refractory MCL.
Read this press release on the MD Anderson Newsroom.
Molecular feature in pancreatic cancer precursor lesions may predict aggressiveness
Early detection of localized pancreatic cancer improves survival outcomes, but detecting indolent – or potentially inconsequential tumors – can lead to overdiagnosis. Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions with the potential to become malignant, but little is known about the mechanisms driving their pathogenesis and progression. To detect possible molecular features of these lesions, researchers led by Anirban Maitra, M.B.B.S., used spatial transcriptomic profiling on pancreatic tissue samples derived from low- and high-grade IPMNs as well as IPMN-associated pancreatic cancers. The study identified NKX6-2 as an important transcription factor driving gastric differentiation of IPMN, which is a marker of biological indolence. Further investigation showed that NKX6-2 overexpression resulted in indolent phenotypes in preclinical models, while NKX6-2 loss of was associated with an aggressive gene signature and histological progression. This study highlights NKX6-2 as a potential biomarker to assist with risk stratification of patients with pancreatic cancer precursor lesions. Learn more in Cancer Discovery.
Study identifies structure and function of breast and ovarian cancer susceptibility gene
RAD51C is a known breast and ovarian cancer susceptibility gene associated with treatment resistance, but neither its protein structure nor the significance of certain mutations is fully understood. Using CRISPR/Cas9-edited cells with RAD51C mutations, researchers led by John Tainer, Ph.D., and Katharina Schlacher, Ph.D., generated the protein’s crystal structure and identified associated DNA replication functions. The study uncovered distinct regions for binding to the DNA repair protein CX3, emphasizing RAD51C’s role in cancer-relevant DNA replication pathways. This builds upon previous results from the Schlacher lab showing that having a RAD51C mutation in addition to a BRCA2 mutation was a strong driver of cancer progression in lab models. The study provides further insights into the molecular features of tumors that resemble BRCA 1/2 mutant tumors, which are particularly sensitive to PARP inhibitors. It also highlights the potential for using RAD51C mutations in patient risk stratification and treatment response predictions. Learn more in Nature Communications.
Targeting polyploid giant cancer cells may help to overcome treatment resistance in ovarian cancer
Polyploid giant cancer cells (PGCCs) can give rise to therapy-resistant cells in various types of solid tumors, but their association with olaparib-resistance in high-grade serous carcinomas (HGSCs) – the most common type of ovarian cancer – is unknown. Researchers led by Jinsong Liu, M.D., Ph.D., and Anil K. Sood, M.D., examined PGCCs in various preclinical ovarian cancer models, including olaparib-resistant cells from tumors with and without BRCA and p53 mutations. Using time-lapse photography, the researchers showed that PGCCs were more common in olaparib-resistant tumors regardless of mutation, and these PGCCs were more likely to become senescent, or stop dividing, with olaparib treatment. However, these seemingly dead cells could give rise to viable, therapy-resistant cells via non-traditional pathways. Adding mifepristone to olaparib blocked the formation and survival of these PGCCs, eliminating tumors in lab models. The study highlights the potential of targeting PGCCs to overcome treatment resistance in patients with ovarian cancer. Learn more in Science Advances.
Rectal cancer patients under 50 have unique tumor microbiome signatures
The incidence of young-onset rectal cancer is on the rise in patients under the age of 50, but the underlying reasons remain unclear. To gain a better understanding of these tumors and their response to treatment, Nancy You, M.D., and colleagues investigated rectal tumor samples collected before neoadjuvant therapy. The researchers analyzed 107 tumor samples and observed unique tumor microbiome signatures in patients younger than 50 compared to those over 50 years old. Interestingly, failure to achieve a major pathological response was associated with the presence of oral bacteria in tumors. These findings highlight the need for further research to explore these associations and suggest the potential to improve current treatment approaches by altering the microbiome, particularly for younger patients. Learn more in Annals of Surgery.
Phosphorylation of DICER1 is prognostic biomarker for metastatic lung cancer
Metastatic lung cancer is the leading cause of cancer-related mortality, so it is important to understand the early genetic and epigenetic changes that can lead to tumor progression. Phosphorylation of the DICER1 enzyme by the KRAS pathway causes its nuclear translocation in human primary lung tumors, suggesting a potential role in metastasis. Researchers led by Swathi Arur, Ph.D., discovered that phosphorylated DICER1 promotes late-stage tumor progression in lab models with oncogenic KRAS, independent of microRNA production or epithelial-to-mesenchymal transition. Instead, DICER1 phosphorylation activated expression of gastric genes in advanced tumors, resulting in more open chromatin and a corresponding lineage switch that allowed tumor cells to spread more easily. The study identified phosphorylated DICER1 as a biomarker for early metastatic disease and suggests the enzyme may be a potential therapeutic target. Learn more in Science Advances.
Researchers develop integrative machine learning model to better predict outcomes in patients with MCL
Mantle cell lymphoma (MCL) is a rare, incurable B-cell cancer with a wide range of potential clinical outcomes, highlighting a need for better prognostic tools. Using multiple classification models, researchers led by Ken Chen, Ph.D., and Michael Wang, M.D., were able to better predict outcomes for patients with MCL. The researchers developed and used a machine learning gradient-boosted model to analyze an extensive database of 862 patients diagnosed with MCL between 2014 and 2022. The integrative prognostic model incorporated baseline demographic, clinicopathological, cytogenetic and genomic data. Using machine learning models allowed researchers to include and interpret thousands of variables that are not used in traditional statistical methods. The findings demonstrate the clinical value and importance of complex machine learning models incorporating multiple features including molecular features, such as TP53 mutations. Learn more in Cancer Research Communications.
Acalabrutinib monotherapy effective in patients with relapsed/refractory MCL
Mantle cell lymphoma (MCL) is considered a difficult-to-treat and aggressive lymphoma, with many patients experiencing recurrent relapses. In a new Phase II study led by Michael Wang, M.D., researchers found that acalabrutinib, a Bruton Tyrosine Kinase inhibitor, was safe and highly active in patients with relapsed/refractory (R/R) MCL. After median follow-up of 38.1 months in 124 patients, the overall response rate was 81.5% and complete response rate was 47.6%. Median progression-free survival was 22 months and median overall survival was 59.2 months. Side effects were consistent with previously reported data. These data suggest further investigation of acalabrutinib is warranted for patients with R/R MCL, including those with poor prognostic factors. Trials evaluating acalabrutinib in combination with other agents in MCL are ongoing. Learn more in Haematologica.
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