Combinations of Low-Frequency Genetic Variants Might Predispose to Familial Pancreatic Cancer

Medulloblastoma and other neoplasms in patients with heterozygous germline SUFU variants: A scoping review

In 2002, heterozygous suppressor of fused variants (SUFU+/-) in the germline were described to have a tumor suppressor role in the development of pediatric medulloblastoma (MB). Other neoplasms associated with pathologic germline SUFU+/- variants have also been described among patients with basal cell nevus syndrome (BCNS; BCNS is also known as Gorlin syndrome, nevoid basal cell carcinoma [BCC] syndrome or Gorlin-Goltz syndrome; OMIM 109400), an autosomal-dominant cancer predisposition syndrome. The phenotype of patients with germline SUFU+/- variants is very poorly characterized due to a paucity of large studies with long-term follow-up. As such, there is a clinical need to better characterize the spectrum of neoplasms among patients with germline SUFU+/- variants so that clinicians can provide accurate counseling and optimize tumor surveillance strategies. The objective of this study is to perform a scoping review to map the evidence on the rate of medulloblastoma and to describe the spectrum of other neoplasms among patients with germline SUFU+/- variants. A review of all published literature in PubMed (MEDLINE), EMBASE, Cochrane, and Web of Science were searched from the beginning of each respective database until October 9, 2021. Studies of pediatric and adult patients with a confirmed germline SUFU+/- variant who were evaluated for the presence of any neoplasm (benign or malignant) were included. There were 176 patients (N = 30 studies) identified with a confirmed germline SUFU+/- variant who met inclusion criteria. Data were extracted from two cohort studies, two case-control studies, 18 case series, and eight case reports. The median age at diagnosis of a germline SUFU+/- variant was 4.5 years where 44.4% identified as female and 13.4% of variants were de novo. There were 34 different neoplasms (benign and malignant) documented among patients with confirmed germline SUFU+/- variants, and the most common were medulloblastoma (N = 59 patients), BCC (N = 21 patients), and meningioma (N = 19 patients). The median age at medulloblastoma diagnosis was 1.42 years (range 0.083-3; interquartile range 1.2). When data were available for these three most frequent neoplasms (N = 95 patients), 31 patients (32.6%) had neither MB, BCC nor meningioma; 51 patients (53.7%) had one of medulloblastoma or BCC or meningioma; eight patients (8.4%) had two of medulloblastoma or BCC or meningioma, and five patients (5.3%) had medulloblastoma and BCC and meningioma. This is the first study to synthesize the data on the frequency and spectrum of neoplasms specifically among patients with a confirmed germline SUFU+/- variant. This scoping review is a necessary step forward in optimizing evidence-based tumor surveillance strategies for medulloblastoma and estimating the risk of other neoplasms that could impact patient outcomes.

Understanding the Genetic Landscape of Pancreatic Ductal Adenocarcinoma to Support Personalized Medicine: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. While population-wide screening recommendations for PDAC in asymptomatic individuals are not achievable due to its relatively low incidence, pancreatic cancer surveillance programs are recommended for patients with germline causative variants in PDAC susceptibility genes or a strong family history. In this study, we sought to determine the prevalence and significance of germline alterations in major genes (ATM, BRCA1, BRCA2, CDKN2A, EPCAM, MLH1, MSH2, MSH6, PALB2, PMS2, STK11, TP53) involved in PDAC susceptibility. We performed a systematic review of PubMed publications reporting germline variants identified in these genes in PDAC patients. Overall, the retrieved articles included 1493 PDAC patients. A high proportion of these patients (n = 1225/1493, 82%) were found to harbor alterations in genes (ATM, BRCA1, BRCA2, PALB2) involved in the homologous recombination repair (HRR) pathway. Specifically, the remaining PDAC patients were reported to carry alterations in genes playing a role in other cancer pathways (CDKN2A, STK11, TP53; n = 181/1493, 12.1%) or in the mismatch repair (MMR) pathway (MLH1, MSH2, MSH6, PMS2; n = 87/1493, 5.8%). Our findings highlight the importance of germline genetic characterization in PDAC patients for better personalized targeted therapies, clinical management, and surveillance.

Anlotinib plus icotinib as a potential treatment option for EGFR-mutated advanced non-squamous non-small cell lung cancer with concurrent mutations: final analysis of the prospective phase 2, multicenter ALTER-L004 study

BACKGROUND

Non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation and concurrent mutations have a poor prognosis. This study aimed to examine anlotinib plus icotinib as a first-line treatment option for advanced NSCLC carrying EGFR mutation with or without concurrent mutations.

METHODS

This phase 2, single-arm, multicenter trial (ClinicalTrials.gov NCT03736837) was performed at five hospitals in China from December 2018 to November 2020. Non-squamous NSCLC cases with EGFR-sensitizing mutations were treated with anlotinib and icotinib. The primary endpoint was progression-free survival (PFS). Secondary endpoints included the objective response rate (ORR), disease control rate (DCR), overall survival (OS), and toxicity.

RESULTS

Sixty participants were enrolled, including 31 (52%) and 29 (48%) with concurrent mutations and pathogenic concurrent mutations, respectively. The median follow-up was 26.9 (range, 15.0-38.9) months. ORR and DCR were 68.5% and 98.2%, respectively. Median PFS was 15.1 (95%CI: 12.6-17.6) months which met the primary endpoint, median DoR was 13.5 (95%CI: 10.0-17.1) months, and median OS was 30.0 (95%CI: 25.5-34.5) months. Median PFS and OS in patients with pathogenic concurrent mutations were 15.6 (95%CI: 12.5-18.7) months and not reached (95%CI: 17.46 months to not reached), respectively. All patients experienced TRAEs, including 26 (43%) and 1 (1.7%) who had grade ≥ 3 and serious treatment-related adverse events (TRAEs).

CONCLUSIONS

Anlotinib combined with icotinib was effective and well-tolerated as a first-line treatment option for EGFR mutation-positive advanced NSCLC with or without concurrent mutations.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03736837.

Characteristics of familial pancreatic cancer families with additional colorectal carcinoma

Familial pancreatic cancer (FPC) is a rare hereditary tumor entity with broad phenotypic heterogeneity, including colorectal carcinoma (CRC) in some families. The underlying factors for this co-occurrence are still not well evaluated. FPC families in the National Case Collection of Familial Pancreatic Cancer with an additional occurrence of CRC were analyzed regarding the phenotype, genotype and recommendation for a clinical screening program. The total cohort of 272 FPC families included 30 (11%) families with at least one CRC case. The proportion of affected family members with PDAC was 16.1% (73/451) compared to 9.3% of family members with CRC (42/451, p < 0.01). Females were affected with PDAC in 49% (36/73) and CRC in 38% (16/42). The median age of PDAC was 63 compared to 66 years in CRC, whereas 8 (26.6%) of families had an early onset of PDAC and 2 (6.7%) of CRC. Seventeen families had 2 or more affected generations with PDAC and 6 families with CRC. Eleven (9.6%) of affected patients had both PDAC and CRC. Potentially causative germline mutations (2 ATM, 1 CDKN2a, 1 MLH1, 1 PALB2) were detected in 5 of 18 (27.7%) analyzed cases. These findings provide a step forward to include the phenotypic and genotypic characteristics of FPC-CRC families for the genetic counseling and management of these families. Nevertheless, results need to be verified in a larger patient cohort beforehand.

Proteomics biomarker discovery for individualized prevention of familial pancreatic cancer using statistical learning

BACKGROUND

The low five-year survival rate of pancreatic ductal adenocarcinoma (PDAC) and the low diagnostic rate of early-stage PDAC via imaging highlight the need to discover novel biomarkers and improve the current screening procedures for early diagnosis. Familial pancreatic cancer (FPC) describes the cases of PDAC that are present in two or more individuals within a circle of first-degree relatives. Using innovative high-throughput proteomics, we were able to quantify the protein profiles of individuals at risk from FPC families in different potential pre-cancer stages. However, the high-dimensional proteomics data structure challenges the use of traditional statistical analysis tools. Hence, we applied advanced statistical learning methods to enhance the analysis and improve the results' interpretability.

METHODS

We applied model-based gradient boosting and adaptive lasso to deal with the small, unbalanced study design via simultaneous variable selection and model fitting. In addition, we used stability selection to identify a stable subset of selected biomarkers and, as a result, obtain even more interpretable results. In each step, we compared the performance of the different analytical pipelines and validated our approaches via simulation scenarios.

RESULTS

In the simulation study, model-based gradient boosting showed a more accurate prediction performance in the small, unbalanced, and high-dimensional datasets than adaptive lasso and could identify more relevant variables. Furthermore, using model-based gradient boosting, we discovered a subset of promising serum biomarkers that may potentially improve the current screening procedure of FPC.

CONCLUSION

Advanced statistical learning methods helped us overcome the shortcomings of an unbalanced study design in a valuable clinical dataset. The discovered serum biomarkers provide us with a clear direction for further investigations and more precise clinical hypotheses regarding the development of FPC and optimal strategies for its early detection.

Interplay between MAP kinases and tumor microenvironment: Opportunity for immunotherapy in pancreatic cancer

Pancreatic Ductal Adenocarcinoma (PDAC), commonly called pancreatic cancer, is aggressive cancer usually detected at a late stage, limiting treatment options with modest clinical responses. It is projected that by 2030, PDAC will be the second most common cause of cancer-related mortality in the United States. Drug resistance in PDAC is common and significantly affects patients' overall survival (OS). Oncogenic KRAS mutations are nearly uniform in PDAC, affecting over 90% of patients. However, effective drugs directed to target prevalent KRAS mutants in pancreatic cancer are not in clinical practice. Accordingly, efforts are continued on identifying alternative druggable target(s) or approaches to improve patient outcomes with PDAC. In most PDAC cases, the KRAS mutations turn-on the RAF-MEK-MAPK pathways, leading to pancreatic tumorigenesis. The MAPK signaling cascade (MAP4K→MAP3K→MAP2K→MAPK) plays a central role in the pancreatic cancer tumor microenvironment (TME) and chemotherapy resistance. The immunosuppressive pancreatic cancer TME is another unfavorable factor affecting the therapeutic efficacy of chemotherapy and immunotherapy. The immune checkpoint proteins (ICPs), including CTLA-4, PD-1, PD-L1, and PD-L2, are critical players in T cell dysfunction and pancreatic tumor cell growth. Here, we review the activation of MAPKs, a molecular trait of KRAS mutations and their impact on pancreatic cancer TME, chemoresistance, and expression of ICPs that could influence the clinical outcomes in PDAC patients. Therefore, understanding the interplay between MAPK pathways and TME could help to design rational therapy combining immunotherapy and MAPK inhibitors for pancreatic cancer treatment.

Protective Prognostic Biomarkers Negatively Correlated with Macrophage M2 Infiltration in Low-Grade Glioma

Tumor-associated Macrophages (TAMs) play a vital role in the progression of glioma. Macrophage M2 has been confirmed to promote immunosuppression and proliferation of low-grade glioma (LGG). Here, we searched for genes negatively correlated with Macrophages M2 by bioinformatical methods and investigated their protective ability for prognosis. LGG and adjacent normal samples were screened out in TCGA and three GEO datasets. 326 overlapped differentially expressed genes were calculated, and their biological functions were investigated by Go and KEGG analyses. Macrophage M2 accounted for the highest proportion among all 22 immune cells by CIBERSORT deconvolution algorithm. The proportion of Macrophage M2 in LGG was also higher than that in normal tissue according to several deconvolution algorithms. 43 genes in the blue module negatively correlated with Macrophage M2 infiltration were identified by weighted gene coexpression network analysis (WGCNA). Through immune infiltration and correlation analysis, FGFBP3, VAX2, and SHD were selected and they were enriched in G protein-coupled receptors' signaling regulation and cytokine receptor interaction. They could prolong the overall and disease-free survival time. Univariate and multivariate Cox regression analyses were applied to evaluate prognosis prediction ability. Interestingly, FGFBP3 and AHD were independent prognostic predictors. A nomogram was drawn, and its 1-year, 3-year, and 5-year survival prognostic value was verified by ROC curves and calibration plots. In conclusion, FGFBP3, VAX2, and SHD were protective prognostic biomarkers against Macrophage M2 infiltration in low-grade glioma. The FGFBP3 and SHD were independent factors to effectively predict long-term survival probability.