Electronic health intervention to manage symptoms of immunotherapy in patients with cancer (SOFIA): Results from a randomized controlled pilot trial.

BACKGROUND: For patients receiving immune checkpoint inhibitors, early detection of immune-related adverse events (irAEs) is critical for one's safety. To this end, a smartphone app (SOFIA) was developed that featured the assessment of electronic patient-reported outcomes (ePROs) focusing on irAEs as well as a set of comprehensive supportive information. Its feasibility and preliminary efficacy were evaluated in a randomized controlled trial (RCT). METHODS: Patients who received immune checkpoint inhibition therapy were randomly assigned to an intervention group (IG) or a control group (CG; care as usual). During the 12-week intervention period, IG patients used SOFIA to report twice weekly ePROs and receive cancer- and immunotherapy-relevant contents. Before a patient's next clinical visit, the physician in charge was given the ePRO reports. The primary objective was to test the feasibility of SOFIA. Furthermore, the preliminary efficacy of SOFIA for health-related quality of life (HRQOL), psychosocial outcomes, and medical data was examined. Clinical outcomes were assessed at baseline (T0), post-intervention (T1), and a 3-month follow-up (T2). RESULTS: Seventy-one patients were randomized to the IG (n = 34) or the CG (n = 37). SOFIA showed high feasibility and acceptance. At T1, patients in the IG reported significantly better HRQOL and role functioning and less depression, distress, and appetite loss. No significant differences were revealed regarding medical data, the utilization of supportive care services, or survival. CONCLUSIONS: SOFIA showed high feasibility and acceptance and improved HRQOL and psychosocial outcomes. These results suggest further evaluation of efficacy in a large-scale confirmatory multicenter RCT.

Graph machine learning for integrated multi-omics analysis.

Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-generating biomarkers for predicting response to therapy, as well as aid in uncovering mechanistic insights into cellular and microenvironmental processes. Many methods for data integration have been developed for the identification of key elements that explain or predict disease risk or other biological outcomes. The heterogeneous graph representation of multi-omics data provides an advantage for discerning patterns suitable for predictive/exploratory analysis, thus permitting the modeling of complex relationships. Graph-based approaches-including graph neural networks-potentially offer a reliable methodological toolset that can provide a tangible alternative to scientists and clinicians that seek ideas and implementation strategies in the integrated analysis of their omics sets for biomedical research. Graph-based workflows continue to push the limits of the technological envelope, and this perspective provides a focused literature review of research articles in which graph machine learning is utilized for integrated multi-omics data analyses, with several examples that demonstrate the effectiveness of graph-based approaches.

Etiology-independent activation of the LTß-LTßR-RELB axis drives aggressiveness and predicts poor prognosis in HCC.

BACKGROUND AND AIMS: HCC is the most common primary liver tumor, with an increasing incidence worldwide. HCC is a heterogeneous malignancy and usually develops in a chronically injured liver. The NF-κB signaling network consists of a canonical and a noncanonical branch. Activation of canonical NF-κB in HCC is documented. However, a functional and clinically relevant role of noncanonical NF-κB and its downstream effectors is not established. APPROACH AND RESULTS: Four human HCC cohorts (total n = 1462) and 4 mouse HCC models were assessed for expression and localization of NF-κB signaling components and activating ligands. In vitro , NF-κB signaling, proliferation, and cell death were measured, proving a pro-proliferative role of v-rel avian reticuloendotheliosis viral oncogene homolog B (RELB) activated by means of NF-κB-inducing kinase. In vivo , lymphotoxin beta was identified as the predominant inducer of RELB activation. Importantly, hepatocyte-specific RELB knockout in a murine HCC model led to a lower incidence compared to controls and lower maximal tumor diameters. In silico , RELB activity and RELB-directed transcriptomics were validated on the The Cancer Genome Atlas HCC cohort using inferred protein activity and Gene Set Enrichment Analysis. In RELB-active HCC, pathways mediating proliferation were significantly activated. In contrast to v-rel avian reticuloendotheliosis viral oncogene homolog A, nuclear enrichment of noncanonical RELB expression identified patients with a poor prognosis in an etiology-independent manner. Moreover, RELB activation was associated with malignant features metastasis and recurrence. CONCLUSIONS: This study demonstrates a prognostically relevant, etiology-independent, and cross-species consistent activation of a lymphotoxin beta/LTßR/RELB axis in hepatocarcinogenesis. These observations may harbor broad implications for HCC, including possible clinical exploitation.

Effects of parenteral nutrition + best supportive nutritional care vs. best supportive nutritional care alone on quality of life in patients with pancreatic cancer-a secondary analysis of PANUSCO.

PURPOSE: Parenteral nutrition (PN) can be an effective treatment to improve the nutritional status of patients with pancreatic cancer, but the effects of PN on quality of life (QoL) are still understudied. Therefore, we aimed at investigating whether the best supportive nutritional care (BSNC) in combination with PN at home compared to BSNC alone changed QoL in patients with advanced pancreatic cancer undergoing chemotherapy over a period of 7 weeks. METHODS: n = 12 patients in the PANUSCO study received nutritional counseling only (control group (CG)) and n = 9 patients were also given supportive PN (intervention group (IG)). The primary endpoint was the change of QoL (EORTC-QLQ-C30 and QLQ-PAN26) over 7 weeks between the groups. RESULTS: There was a significant worsening in social functioning in IG (p = 0.031) and a significant difference between groups in change of social functioning (p = 0.020). In all other domains of QoL, there was no significant difference between groups. Within groups, there was a significant improvement in the domain weight loss in IG (p = 0.031), showing that patients were less worried about their weight being too low. Furthermore, there was a significant difference in the change of BW over time between groups (p < 0.001) with IG showing an increase (p = 0.004) and CG showing no change (p = 0.578). CONCLUSION: The administration of PN had in one of five domains negative consequences on QoL. The decision to administer PN should always be made individually and together with the patient, and the impact on QoL should be included in the decision to administer PN.

Interrogating the microenvironmental landscape of tumors with computational image analysis approaches.

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.

Oncological Outcome of Conversion Surgery After Preoperative Chemotherapy for Metastatic Pancreatic Cancer.

OBJECTIVE: To investigate the outcome of conversion surgery in patients with metastatic pancreatic cancer (mPDAC) and to identify patients who may benefit from this approach. BACKGROUND: The role of conversion surgery in patients with mPDAC and exceptional response to chemotherapy remains unclear. METHODS: Patients who underwent surgical exploration for mPDAC following chemotherapy between 2006 and 2019 were included. Data on demographics, oncologic treatment, pathology, and postoperative outcomes were analyzed. Univariate and multivariate survival analyses were performed. RESULTS: Some 173 patients received preoperative chemotherapy and underwent surgical exploration. Ninety-three patients underwent resection of the primary tumor and metastatic sites, 80 patients underwent exploration only. In the resection subgroup, 45 patients had complete pathological response of metastases (ypM0) and 48 patients had residual metastases (ypM1). ypM0 status was associated with lower carcinoembryonic antigen levels and lower ypN stage. Overall survival after resection was 25.5 months in ypM0, 10.7 months in ypM1, and 8.1 months in patients without resection ( P <0.001). Additional adjuvant chemotherapy was significantly associated with prolonged survival in resected patients (29.0 vs 14.8 mo, P =0.024) as well as in ypM0 (29.1 vs 19.2 mo, P =0.047). Multivariable analysis identified conversion surgery, carbohydrate antigen 19-9 (CA19-9) and time of resection as independent prognostic markers for the entire cohort. CA19-9, ypM0 and adjuvant treatment were independent predictors of survival in the resection subgroup. CONCLUSION: In patients with mPDAC and ypM0 status after chemotherapy, surgical resection is associated with encouraging survival. mPDAC patients with exceptional response to chemotherapy may be candidates for exploration and for resection in ypM0. Adjuvant chemotherapy may provide an additional survival advantage.

BAP1 and PTEN mutations shape the immunological landscape of clear cell renal cell carcinoma and reveal the intertumoral heterogeneity of T cell suppression: a proof-of-concept study.

Clear cell renal cell carcinoma (ccRCC) is an immunologically vulnerable tumor entity, and immune checkpoint inhibitors are now widely used to treat patients with advanced disease. Whether and to what extent immune responses in ccRCC are shaped by genetic alterations, however, is only beginning to emerge. In this proof-of-concept study, we performed a detailed correlative analysis of the mutational and immunological landscapes in a series of 23 consecutive kidney cancer patients. We discovered that a high infiltration with CD8 + T cells was not dependent on the number of driver mutations but rather on the presence of specific mutational events, namely pathogenic mutations in PTEN or BAP1. This observation encouraged us to compare mechanisms of T cell suppression in the context of four different genetic patterns, i.e., the presence of multiple drivers, a PTEN or BAP1 mutation, or the absence of detectable driver mutations. We found that ccRCCs harboring a PTEN or BAP1 mutation showed the lowest level of Granzyme B positive tumor-infiltrating lymphocytes (TILs). A multiplex immunofluorescence analysis revealed a significant number of CD8 + TILs in the vicinity of CD68 + macrophages/monocytes in the context of a BAP1 mutation but not in the context of a PTEN mutation. In line with this finding, direct interactions between CD8 + TILs and CD163 + M2-polarized macrophages were found in BAP1-mutated ccRCC but not in tumors with other mutational patterns. While an absence of driver mutations was associated with more CD8 + TILs in the vicinity of FOXP3 + Tregs and CD68 + monocytes/macrophages, the presence of multiple driver mutations was, to our surprise, not found to be strongly associated with immunosuppressive mechanisms. Our results highlight the role of genetic alterations in shaping the immunological landscape of ccRCC. We discovered a remarkable heterogeneity of mechanisms that can lead to T cell suppression, which supports the need for personalized immune oncological approaches.

Knowledge bases and software support for variant interpretation in precision oncology.

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.

A precision-based exercise program for patients with multiple myeloma.

OBJECTIVES: Aim of this study was to retrospectively evaluate an interdisciplinary consultation followed by a precision-based exercise program (PEP) for myeloma patients with stable and unstable bone lesions. METHODS: Data of myeloma patients (n = 100) who received a PEP according to an orthopedic evaluation were analyzed. Bone stability was assessed by established scoring systems (Spinal Instability Neoplastic Score [SINS], Mirels' score). All patients with stable and unstable osteolyses received a PEP and n = 91 were contacted for a follow-up interview. RESULTS: In 60% of patients at least one osteolysis of the spine was considered potentially unstable or unstable. Following consultation, the number of patients performing resistance training could be significantly increased (≥2 sessions/week, 55%). Musculoskeletal pain was reported frequently. At the follow-up interview, 75% of patients who performed PEP stated that painful symptoms could be effectively alleviated by exercise. Moreover, only patients who exercised regularly discontinued pain medication. No injuries were reported in association with PEP. CONCLUSION: We were able to demonstrate that individualized resistance training is implementable and safe for myeloma patients. By means of a PEP, patients' self-efficacy in managing musculoskeletal pain was enhanced and pain medication could be reduced.

Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology.

Deep learning is a powerful tool in computational pathology: it can be used for tumor detection and for predicting genetic alterations based on histopathology images alone. Conventionally, tumor detection and prediction of genetic alterations are two separate workflows. Newer methods have combined them, but require complex, manually engineered computational pipelines, restricting reproducibility and robustness. To address these issues, we present a new method for simultaneous tumor detection and prediction of genetic alterations: The Slide-Level Assessment Model (SLAM) uses a single off-the-shelf neural network to predict molecular alterations directly from routine pathology slides without any manual annotations, improving upon previous methods by automatically excluding normal and non-informative tissue regions. SLAM requires only standard programming libraries and is conceptually simpler than previous approaches. We have extensively validated SLAM for clinically relevant tasks using two large multicentric cohorts of colorectal cancer patients, Darmkrebs: Chancen der Verhütung durch Screening (DACHS) from Germany and Yorkshire Cancer Research Bowel Cancer Improvement Programme (YCR-BCIP) from the UK. We show that SLAM yields reliable slide-level classification of tumor presence with an area under the receiver operating curve (AUROC) of 0.980 (confidence interval 0.975, 0.984; n = 2,297 tumor and n = 1,281 normal slides). In addition, SLAM can detect microsatellite instability (MSI)/mismatch repair deficiency (dMMR) or microsatellite stability/mismatch repair proficiency with an AUROC of 0.909 (0.888, 0.929; n = 2,039 patients) and BRAF mutational status with an AUROC of 0.821 (0.786, 0.852; n = 2,075 patients). The improvement with respect to previous methods was validated in a large external testing cohort in which MSI/dMMR status was detected with an AUROC of 0.900 (0.864, 0.931; n = 805 patients). In addition, SLAM provides human-interpretable visualization maps, enabling the analysis of multiplexed network predictions by human experts. In summary, SLAM is a new simple and powerful method for computational pathology that could be applied to multiple disease contexts. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Severe Dysbiosis and Specific Haemophilus and Neisseria Signatures as Hallmarks of the Oropharyngeal Microbiome in Critically Ill Coronavirus Disease 2019 (COVID-19) Patients.

BACKGROUND: At the entry site of respiratory virus infections, the oropharyngeal microbiome has been proposed as a major hub integrating viral and host immune signals. Early studies suggested that infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are associated with changes of the upper and lower airway microbiome, and that specific microbial signatures may predict coronavirus disease 2019 (COVID-19) illness. However, the results are not conclusive, as critical illness can drastically alter a patient's microbiome through multiple confounders. METHODS: To study oropharyngeal microbiome profiles in SARS-CoV-2 infection, clinical confounders, and prediction models in COVID-19, we performed a multicenter, cross-sectional clinical study analyzing oropharyngeal microbial metagenomes in healthy adults, patients with non-SARS-CoV-2 infections, or with mild, moderate, and severe COVID-19 (n = 322 participants). RESULTS: In contrast to mild infections, patients admitted to a hospital with moderate or severe COVID-19 showed dysbiotic microbial configurations, which were significantly pronounced in patients treated with broad-spectrum antibiotics, receiving invasive mechanical ventilation, or when sampling was performed during prolonged hospitalization. In contrast, specimens collected early after admission allowed us to segregate microbiome features predictive of hospital COVID-19 mortality utilizing machine learning models. Taxonomic signatures were found to perform better than models utilizing clinical variables with Neisseria and Haemophilus species abundances as most important features. CONCLUSIONS: In addition to the infection per se, several factors shape the oropharyngeal microbiome of severely affected COVID-19 patients and deserve consideration in the interpretation of the role of the microbiome in severe COVID-19. Nevertheless, we were able to extract microbial features that can help to predict clinical outcomes.

Actual Five-year Survival After Upfront Resection for Pancreatic Ductal Adenocarcinoma: Who Beats the Odds?

OBJECTIVE: To determine actual five-year survival (5YS) rates associated with a strategy of upfront surgery and adjuvant therapy in pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: The rate of actual 5YS in PDAC remains controversial. Available data is restricted to cohorts acquired over several decades and series of resection after patient selection by neoadjuvant therapy. METHODS: All patients undergoing upfront resection for resectable and borderline-resectable PDAC from 10/2001 to 12/2011 were identified from a prospective database. Actual overall survival was assessed after a follow-up of at least 5 years. Uni- and multivariable logistic regression analyses were performed. RESULTS: Median survival of 937 patients was 22.1 months. The actual 5YS rate was 17.0% (n = 159) including 89 (9.5%) patients without evidence of disease >5 years after resection. 5YS rates in patients with or without adjuvanttherapy were 18.8% vs. 12.2%, respectively. Tumorgrading, number of positive lymph nodes, a context of intraductal papillary mucinous neoplasia, and vascular resections were independently associated with 5YS. Patient-related parameters and CA 19-9 levels were associated with observed survival up to 3 years, but lost relevance thereafter. The extent of lymph node involvement was the strongest predictor of 5YS. Patients with pN0R0 had a 5YS rate of 38.2%. in patients with exclusively favorable factors the observed 5YS rate was above 50%. CONCLUSIONS: This is the largest series of long-term survivors with histologically confirmed PDAC. With upfront resection and adjuvant therapy an actual overall 5YS rate of 18.8% can be expected. in favorable subgroups actual 5YS is above 50%.

Bcl-xL as prognostic marker and potential therapeutic target in cholangiocarcinoma.

Intrahepatic, perihilar, and distal cholangiocarcinoma (iCCA, pCCA, dCCA) are highly malignant tumours with increasing mortality rates due to therapy resistances. Among the mechanisms mediating resistance, overexpression of anti-apoptotic Bcl-2 proteins (Bcl-2, Bcl-xL , Mcl-1) is particularly important. In this study, we investigated whether antiapoptotic protein patterns are prognostically relevant and potential therapeutic targets in CCA. Bcl-2 proteins were analysed in a pan-cancer cohort from the NCT/DKFZ/DKTK MASTER registry trial (n = 1140, CCA n = 72) via RNA-sequencing and transcriptome-based protein activity interference revealing high ranks of CCA for Bcl-xL and Mcl-1. Expression of Bcl-xL , Mcl-1, and Bcl-2 was assessed in human CCA tissue and cell lines compared with cholangiocytes by immunohistochemistry, immunoblotting, and quantitative-RT-PCR. Immunohistochemistry confirmed the upregulation of Bcl-xL and Mcl-1 in iCCA tissues. Cell death of CCA cell lines upon treatment with specific small molecule inhibitors of Bcl-xL (Wehi-539), of Mcl-1 (S63845), and Bcl-2 (ABT-199), either alone, in combination with each other or together with chemotherapeutics was assessed by flow cytometry. Targeting Bcl-xL induced cell death and augmented the effect of chemotherapy in CCA cells. Combined inhibition of Bcl-xL and Mcl-1 led to a synergistic increase in cell death in CCA cell lines. Correlation between Bcl-2 protein expression and survival was analysed within three independent patient cohorts from cancer centers in Germany comprising 656 CCA cases indicating a prognostic value of Bcl-xL in CCA depending on the CCA subtype. Collectively, these observations identify Bcl-xL as a key protein in cell death resistance of CCA and may pave the way for clinical application.

Interleukin-2 and Interferon-α for Advanced Renal Cell Carcinoma: Patient Outcomes, Sexual Dimorphism of Responses, and Multimodal Treatment Approaches over a 30-Year Period.

INTRODUCTION: Cytokine-based immunotherapy (IT) has been the mainstay of systemic treatment of advanced renal cell carcinoma (RCC) from the late 1980s until 2007. With the introduction of immune checkpoint inhibitors, a renaissance of immune oncological approaches is rapidly unfolding. MATERIALS AND METHODS: In the present study, we revisited survival outcomes, sexual dimorphism of treatment responses, and the relevance of multimodal treatment approaches over a 30-year period in 156 patients with advanced RCC treated with subcutaneous (s.c.) interleukin-2 (IL-2) and interferon-α (IFN-α) between 1990 and 2009. RESULTS: The median progression-free survival following the first IT was 5.8 months with a wide range from 0 to 197 months. The median overall survival (OS) was 25.8 months and the median cancer-specific survival after tumor nephrectomy was 24.6 months. A group of 29 patients (18.6%) and 11 patients (7.1%) survived longer than 5 and 10 years after surgery, respectively. A difference in the 5-year OS rate between male and female patients was detected (men, 21.6%; women, 11.1%). However, no sex-specific survival advantage was observed after 10 years. CONCLUSIONS: We provide evidence that IT with s.c. IL-2 and IFN-α played a vital role in long-term survivors either by inducing lasting complete remissions or as part of multimodal approaches that allowed patients to survive until novel therapies became available. The implications for current immune oncological treatment approaches are being discussed.

Specific Targeting of Antiapoptotic Bcl-2 Proteins as a Radiosensitizing Approach in Solid Tumors.

Avoidance of therapy-induced apoptosis is a hallmark of acquired resistance towards radiotherapy. Thus, breaking resistance still challenges modern cancer therapy. The Bcl-2 protein family is known for its regulatory role in apoptosis signaling, making Bcl-2, Mcl-1 and Bcl-xL promising targets. This study evaluates the effects of highly specific inhibitors for Bcl-xL (WEHI-539), Bcl-2 (ABT-199) and Mcl-1 (S63845) as radiosensitizers. Covering a broad spectrum of solid tumors, Non-Small-Cell Lung Cancer (NSCLC), Head and Neck Squamous Cell Carcinoma (HNSCC) and synovial sarcoma cell lines were exposed to fractionated radiation as standard therapy with or without Bcl-2 protein inhibition. Protein expression was detected by Western blot and cell death was assessed by flow cytometry measuring apoptosis. In contrast to NSCLC, a high level of Bcl-xL and its upregulation during radiotherapy indicated radioresistance in HNSCC and synovial sarcoma. Radioresistant cell lines across all entities benefited synergistically from combined therapy with Bcl-xL inhibition and fractionated radiation. In NSCLC cell lines, Mcl-1 inhibition significantly augmented radiotherapy independent of the expression level. Our data suggest that among antiapoptotic Bcl-2 proteins, targeting Bcl-xL may break resistance to radiation in HNSCC, synovial sarcoma and NSCLC in vitro. In NSCLC, Mcl-1 might be a promising target that needs further investigation.

PARP inhibition in prostate cancer.

Defects in DNA damage repair genes are more common in prostate cancer than previously thought. These alterations provide an opportunity for precision oncology approaches and a number of studies have now shown that PARP inhibitors can have significant antitumor activity in men with DNA damage repair-deficient metastatic castration-resistant prostate cancer. This review summarizes the key clinical trials related to the use of PARP inhibitors in prostate cancer. Besides clinical outcomes, toxicity, and PARP inhibitor resistance, the role of different DNA repair genes in the response to PARP inhibition will be discussed.

Poly(ADP-ribose) polymerase inhibition in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with limited treatment options. Recently, the poly(ADP-ribose) polymerase inhibitor (PARPi) olaparib has been approved for maintenance therapy after successful platinum-based chemotherapy in patients with germline mutations in BRCA1 and BRCA2. Approval was based on the POLO study that has shown a significant improvement in progression-free survival for patients with metastatic PDAC after at least 4 months of platinum-based chemotherapy. Hopefully, this first biomarker-directed targeted therapy for a relevant subgroup of pancreatic cancer patients is only the beginning of an era of personalized therapy for pancreatic cancer. The potential role for PARPi in improving survival in patients with pancreatic cancer containing somatic tumor mutations has yet to be established. Multiple studies investigating whether PARPi therapy might benefit a larger group of pancreatic cancer patients with homologous recombination repair deficiency and whether combinations with chemotherapy, immunotherapy, or small molecules can improve efficacy are currently underway. We here review the molecular basis for PARPi therapy in PDAC patients and recent developments in clinical studies.

68Ga-FAPI-PET/CT in patients with various gynecological malignancies.

PURPOSE: 68Ga-FAPI (fibroblast activation protein inhibitor) is a novel and highly promising radiotracer for PET/CT imaging. The aim of this retrospective analysis is to explore the potential of FAPI-PET/CT in gynecological malignancies. We assessed biodistribution, tumor uptake, and the influence of pre- or postmenopausal status on tracer accumulation in hormone-sensitive organs. Furthermore, a comparison with the current standard oncological tracer 18F-FDG was performed in selected cases. PATIENTS AND METHODS: A total of 31 patients (median age 59.5) from two centers with several gynecological tumors (breast cancer; ovarian cancer; cervical cancer; endometrial cancer; leiomyosarcoma of the uterus; tubal cancer) underwent 68Ga-FAPI-PET/CT. Out of 31 patients, 10 received an additional 18F-FDG scan within a median time interval of 12.5 days (range 1-76). Tracer uptake was quantified by standardized uptake values (SUV)max and (SUV)mean, and tumor-to-background ratio (TBR) was calculated (SUVmax tumor/ SUVmean organ). Moreover, a second cohort of 167 female patients with different malignancies was analyzed regarding their FAPI uptake in normal hormone-responsive organs: endometrium (n = 128), ovary (n = 64), and breast (n = 147). These patients were categorized by age as premenopausal (<35 years; n = 12), postmenopausal (>65 years; n = 68), and unknown menstrual status (35-65 years; n = 87), followed by an analysis of FAPI uptake of the pre- and postmenopausal group. RESULTS: In 8 out of 31 patients, the primary tumor was present, and all 31 patients showed lesions suspicious for metastasis (n = 81) demonstrating a high mean SUVmax in both the primary (SUVmax 11.6) and metastatic lesions (SUVmax 9.7). TBR was significantly higher in 68Ga-FAPI compared to 18F-FDG for distant metastases (13.0 vs. 5.7; p = 0.047) and by trend for regional lymph node metastases (31.9 vs 27.3; p = 0.6). Biodistribution of 68Ga-FAPI-PET/CT presented significantly lower uptake or no significant differences in 15 out of 16 organs, compared to 18F-FDG-PET/CT. The highest uptake of all primary lesions was obtained in endometrial carcinomas (mean SUVmax 18.4), followed by cervical carcinomas (mean SUVmax 15.22). In the second cohort, uptake in premenopausal patients differed significantly from postmenopausal patients in endometrium (11.7 vs 3.9; p < 0.0001) and breast (1.8 vs 1.0; p = 0.004), whereas no significant difference concerning ovaries (2.8 vs 1.6; p = 0.141) was observed. CONCLUSION: Due to high tracer uptake resulting in sharp contrasts in primary and metastatic lesions and higher TBRs than 18F-FDG-PET/CT, 68Ga-FAPI-PET/CT presents a promising imaging method for staging and follow-up of gynecological tumors. The presence or absence of the menstrual cycle seems to correlate with FAPI accumulation in the normal endometrium and breast. This first investigation of FAP ligands in gynecological tumor entities supports clinical application and further research in this field.

Rapid MALDI-MS Assays for Drug Quantification in Biological Matrices: Lessons Learned, New Developments, and Future Perspectives.

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has rarely been used in the field of therapeutic drug monitoring, partly because of the complexity of the ionization processes between the compounds to be quantified and the many MALDI matrices available. The development of a viable MALDI-MS method that meets regulatory guidelines for bioanalytical method validation requires prior knowledge of the suitability of (i) the MALDI matrix with the analyte class and properties for ionization, (ii) the crystallization properties of the MALDI matrix with automation features, and (iii) the MS instrumentation used to achieve sensitive and specific measurements in order to determine low pharmacological drug concentrations in biological matrices. In the present hybrid article/white paper, we review the developments required for the establishment of MALDI-MS assays for the quantification of drugs in tissues and plasma, illustrated with concrete results for the different steps. We summarize the necessary parameters that need to be controlled for the successful development of fully validated MALDI-MS methods according to regulatory authorities, as well as currently unsolved problems and promising ways to address them. Finally, we propose an expert opinion on future perspectives and needs in order to establish MALDI-MS as a universal method for therapeutic drug monitoring.

Cancer surveillance and distress among adult pathogenic TP53 germline variant carriers in Germany: A multicenter feasibility and acceptance survey.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a high-risk cancer predisposition syndrome caused by pathogenic germline variants of TP53. Cancer surveillance has noted a significant survival advantage in individuals with LFS; however, little is known about the feasibility, acceptance, and psychosocial effects of such a program. METHODS: Pathogenic TP53 germline variant carriers completed a 7-part questionnaire evaluating sociodemographics, cancer history, surveillance participation, reasons for nonadherence, worries, and distress adapted from the Cancer Worry Scale. Counselees' common concerns and suggestions were assessed in MAXQDA Analytics Pro 12. RESULTS: Forty-nine participants (46 females and 3 males), aged 40.0 ± 12.6 years, formed the study population; 43 (88%) had a personal cancer history (including multiple cancers in 10 [20%]). Forty-three individuals participated (88%) in surveillance during the study or formerly. Willingness to undergo surveillance was influenced by satisfaction with genetic testing and counseling (P = .019 [Fisher-Yates test]) but not by sociodemographics, cancer history, or distress level. Almost one-third of the participants reported logistical difficulties in implementing surveillance because of the high frequency of medical visits, scheduling difficulties, and the travel distance to their surveillance providers. Self-reported distress and perceived emotional burden for family members and partners were moderate (median for self-reported distress, 3.3; median for perceived emotional burden, 3.0). For both, the interquartile range was moderate to very high (2.7-3.7 and 3.0-3.7, respectively). CONCLUSIONS: Individuals with LFS require efficient counseling as well as an accessible, well-organized, interdisciplinary, standardized surveillance program to increase adherence and psychological coping.