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Precise diagnosis and subtyping of kidney tumors are imperative to optimize and personalize treatment decision for patients. Patients with the most common benign renal tumor, renal oncocytomas, may be overtreated with surgical resection because of limited preoperative diagnostic methods that can accurately identify the benign condition with certainty. In this study, desorption electrospray ionization (DESI)-mass spectrometry (MS) imaging was applied to study the metabolic and lipid profiles of various types of renal tissues, including normal kidney, renal oncocytoma, and renal cell carcinomas (RCC). A total of 73,992 mass spectra from 71 patient samples were obtained and used to build predictive models using the least absolute shrinkage and selection operator (Lasso). Overall accuracies of 99.47% per pixel and 100% per patient for prediction of the three tissue types were achieved. In particular, renal oncocytoma and chromophobe RCC, which present the most significant morphologic overlap and are sometimes indistinguishable using histology alone, were also investigated and the predictive models built yielded 100% accuracy in discriminating these tumor types. Discrimination of three subtypes of RCC was also achieved on the basis of DESI-MS imaging data. Importantly, several small metabolites and lipids species were identified as characteristic of individual tissue types and chemically characterized using tandem MS and high mass accuracy measurements. Collectively, our study shows that the metabolic data acquired by DESI-MS imaging in conjunction with statistical modeling allows discrimination of renal tumors and thus has the potential to be used in the clinical setting to improve treatment of patients with kidney tumor.Significance:Metabolic data acquired by mass spectrometry imaging in conjunction with statistical modeling allows discrimination of renal tumors and has the potential to be used in the clinic to improve treatment of patients.

Supplementary Figures and Supplementary Figure legends. Supplementary Fig. 1.- Tandem mass spectrum of m/z 810.527 and the tentative assignment, Supplementary Fig. 2.- Tandem mass spectrum of m/z 723.478 and the tentative assignment, Supplementary Fig. 3.- Comparison of mass spectra of kidney cortex tissue sections from normal patient, Supplementary Fig. 4.- Comparison of mass spectra from normal patients which contain both cortex and medulla, Supplementary Fig. 5.- PCA analysis of normal kidney tissues containing both cortex and medulla and the biplot, Supplementary Fig. 6.- The graphical summary from PCA of cortex and medulla tissue for six selected ions, Supplementary Fig. 7.- Tandem mass spectrum of m/z 887.557 and the tentative assignment, Supplementary Fig. 8.- Tentative peak assignment for m/z 215.032, Supplementary Fig. 9.- Tandem mass spectrum of m/z 175.025 and the tentative assignment, Supplementary Fig. 10.- Tandem mass spectrum of m/z 885.547 and the tentative assignment, Supplementary Fig. 11.- Tandem mass spectrum of m/z 773.532 and the tentative assignment, Supplementary Fig. 12.- Tandem mass spectrum of m/z 766.538 and the tentative assignment, Supplementary Fig. 13.- Tandem mass spectrum of m/z 1035.772 and the tentative assignment, Supplementary Fig. 14.- Tandem mass spectrum of m/z 737.490 and the tentative assignment, Supplementary Fig. 15.- Tandem mass spectrum of m/z 464.314, m/z 697.482, and m/z 842.589 and the tentative assignment, Supplementary Fig. 16.- Tandem mass spectrum of m/z 306.077 and the tentative assignment, Supplementary Fig. 17.- Tandem mass spectrum of m/z 712.485 and the tentative assignment, Supplementary Fig. 18.- Mass spectrometric profile from normal kidney tissue at mass range from m/z 723 to m/z 728, Supplementary Fig. 19.- PCA analysis of averaged mass spectra of ROchRCC tissues and ccRCCppRCC tissues and the biplot. Supplementary Tables. Supplementary Table 1. m/z values selected by the lasso as important for characterizing normal kidney, RO and RCC, Supplementary Table 2. m/z values selected by the lasso as important for characterizing RO and chRCC, Supplementary Table 3. CL and PE related species selected by the lasso for characterizing RO and chRCC, Supplementary Table 4. m/z values selected by the lasso as important for characterizing three renal cancer subtypes (ccRCC, chRCC, and ppRCC), Supplementary Table 5. The top loading plots of PC1 and PC2 for PCA of cortex and medulla in normal kidney tissue, Supplementary Table 6. The top loading plots of PC1 and PC2 for PCA of ROchRCC vs ppRCCccRCC. Supplementary Data Supplementary Results, Supplementary Methods, Supplementary Discussion

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat and fish types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 s per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Predictors of meat type selected included several molecules previously reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine, and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is a powerful alternative analytical method for meat analysis and investigation of meat fraud.

BACKGROUNDDistinguishing adenocarcinoma and squamous cell carcinoma subtypes of non-small cell lung cancers is critical to patient care. Preoperative minimally-invasive biopsy techniques, such as fine needle aspiration (FNA), are increasingly used for lung cancer diagnosis and subtyping. Yet, histologic distinction of lung cancer subtypes in FNA material can be challenging. Here, we evaluated the usefulness of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to diagnose and differentiate lung cancer subtypes in tissues and FNA samples.METHODSDESI-MSI was used to analyze 22 normal, 26 adenocarcinoma, and 25 squamous cell carcinoma lung tissues. Mass spectra obtained from the tissue sections were used to generate and validate statistical classifiers for lung cancer diagnosis and subtyping. Classifiers were then tested on DESI-MSI data collected from 16 clinical FNA samples prospectively collected from 8 patients undergoing interventional radiology guided FNA.RESULTSVarious metabolites and lipid species were detected in the mass spectra obtained from lung tissues. The classifiers generated from tissue sections yielded 100% accuracy, 100% sensitivity, and 100% specificity for lung cancer diagnosis, and 73.5% accuracy for lung cancer subtyping for the training set of tissues, per-patient. On the validation set of tissues, 100% accuracy for lung cancer diagnosis and 94.1% accuracy for lung cancer subtyping were achieved. When tested on the FNA samples, 100% diagnostic accuracy and 87.5% accuracy on subtyping were achieved per-slide.ConclusionsDESI-MSI can be useful as an ancillary technique to conventional cytopathology for diagnosis and subtyping of non-small cell lung cancers.

Complete tumor removal during breast conserving surgery (BCS) remains a challenge for even the most experienced surgeons due to difficulties associated with detecting residual disease at the margin. Additionally, there is limited technology to evaluate resected tissue while the patient is under anesthesia. Mass spectrometry (MS) has been previously used for rapid molecular characterization of healthy and diseased tissue and has shown potential for intraoperative use. We have developed an MS-based technology that couples a handheld and biocompatible device, the MasSpec Pen, to a mass spectrometer for non-destructive ex vivo and in vivo analysis of cancer tissue in a matter of seconds. We have used the MasSpec Pen with multivariate statistical analysis to discriminate the molecular patterns of normal breast and lymph node from invasive cancer tissue, achieving accuracies over 88%. Our results showcase the potential of the MasSpec Pen to provide surgical guidance during BCS. A total of 213 banked human tissues including normal breast and lymph node, IDC, and IDC to lymph node were obtained from the Cooperative Human Tissue Network and stored at -80°C prior to analysis. Samples were then thawed and analyzed using a mass spectrometer coupled to the MasSpec Pen. During MasSpec Pen analysis, a single water droplet is held in contact with the tissue to extract molecules that are then analyzed by a mass spectrometer, yielding a molecular fingerprint. The molecular information obtained is analyzed by the statistical model to provide a predictive diagnosis in seconds. The least absolute shrinkage and selection operator (Lasso) statistical method was used to generate predictive models comprised of molecular features indicative of healthy and diseased tissue. Analyzed regions of tissue were demarcated with a surgical ink marker, snap frozen, and sectioned at a thickness of 5µm. Tissue sections were H&E stained for pathological evaluation. The MasSpec Pen was used to analyze 79 normal and 64 breast cancer tissues. Various molecular species involved in cell metabolism, including metabolites, fatty acids, and glycerophospholipids were observed in the mass spectra. For example, glutamate was detected at a high relative abundance in breast cancer tissue while hexose was detected at a high abundance in normal breast tissue. The primary breast cancer model yielded a sensitivity and specificity over 95% for the training set (n=68) and validation set (n=22). The diagnostic capabilities of the model were further evaluated by predicting on an independent test set of samples (n=53). A sensitivity and specificity of 83.9% and 100% were achieved, demonstrating the ability of the MasSpec Pen to discriminate between normal and cancerous breast tissue. The MasSpec Pen was used to detect metastatic breast cancer in lymph node. Normal lymph nodes (n=26) and nodes with metastatic disease (n=44) were analyzed with the MasSpec Pen. For the metastatic breast cancer model, overall accuracies of 88.7% and 94.1% were achieved for the training set (n=46) and validation set (n=17), respectively. We envision the MasSpec Pen to be used in the operating room (OR) for the in vivo analysis of breast cancer. Recently, we have implemented the MasSpec Pec in the OR to evaluate the feasibility of this technology for intraoperative analysis of breast and lymph node tissue. Similar molecular species are detected in spectra obtained from the in vivo and ex vivo analysis of human breast and lymph node tissue when compared to spectra obtained from banked tissue. Continuous effort is being made to continue patient accrual and testing of the technology. Collectively, these results showcase the capability of the MasSpec Pen for breast cancer detection and its potential as an intraoperative tool for rapid breast cancer diagnosis and surgical margin evaluation during BCS. Citation Format: Kyana Y Garza, Jialing Zhang, John Q Lin, Stacey Carter, James Suliburk, Chandandeep Nagi, Livia S Eberlin. Advanced development of the MasSpec Pen technology to aid in breast cancer surgical margin evaluation and diagnosis during surgery [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-20-04.

Breast cancer resulting from a genetic mutations, such as BRCA1 or BRCA2, is seen in 5 to 10 percent of patients. More widespread genetic testing has increased the number of affected women undergoing prophylactic mastectomy and oophorectomy. Recent studies have yielded mixed results regarding complication rates after combined breast and ovarian operations. The authors compared surgical outcomes of breast operations performed in combination with salpingo-oophorectomies or as separate procedures.The authors retrospectively analyzed surgical complications and length of hospital stay in 145 female patients, from which 87 had undergone combined breast surgery and salpingo-oophorectomy, and 58 had undergone these procedures separately. Multivariate logistic regression models were used to calculate odds ratios and 95 percent confidence intervals.Patients undergoing combined breast and ovarian operations experienced higher rates of overall complications (46.5 percent versus 19 percent; p0.001), infections (22.2 percent versus 8.6 percent; p0.05), and delayed wound healing (13.2 percent versus 0 percent; p0.05) related to the breast surgery, when compared with patients undergoing separate procedures. Multivariate logistic regression analysis confirmed a significant association between combined surgery and overall postoperative complications (OR, 5.87; 95 percent CI, 2.03 to 16.91; p = 0.02). Patients undergoing tissue expander-based breast reconstruction combined with ovarian surgery had significantly longer hospital stays compared to patients undergoing separate procedures (3.5 days versus 1.8 days; p0.001).The authors' data indicate that combining breast and ovarian operations is associated with a higher risk of postoperative complications related to the breast procedure and increases the duration of hospital stay in patients with tissue expander-based reconstructions. The authors' study provides valuable information for preoperative counseling of patients considering both breast and ovarian surgery.Therapeutic, III.

Description, Vitamin D–activated Trem2+ macrophages provide a novel strategy to develop advanced cell therapies for complex wounds., Skin allo- and xenotransplantation are the standard treatment for major burns when donor sites for autografts are not available. The relationship between the immune response to foreign grafts and their impact on wound healing has not been fully elucidated. Here, we investigated changes in collagen architecture after xenogeneic implantation of human biologic scaffolds. We show that collagen deposition in response to the implantation of human split-thickness skin grafts (hSTSGs) containing live cells recapitulates normal skin architecture, whereas human acellular dermal matrix (ADM) grafts led to a fibrotic collagen deposition. We show that macrophage differentiation in response to hSTSG implantation is driven toward regenerative Trem2+ subpopulations and found that hydrogel delivery of these cells significantly accelerated wound closure. Our study identifies the preclinical therapeutic potential of Trem2+ macrophages to mitigate fibrosis and promote wound healing, providing a novel effective strategy to develop advanced cell therapies for complex wounds.

The use of biologic mesh to reinforce the abdominal wall in ventral hernia repair has been proposed as a viable alternative to synthetic mesh, particularly for high-risk patients and in contaminated settings. However, a comparison of clinical outcomes between the currently available biologic mesh types has yet to be performed.We performed a retrospective analysis of 141 patients who had undergone ventral hernia repair with biologic mesh, including noncross-linked porcine ADM (NC-PADM) (n = 51), cross-linked porcine ADM (C-PADM) (n = 17), reinforced biologic ovine rumen (RBOR) (n = 36), and bovine ADM (BADM) (n = 37) at the Stanford University Medical Center between 2002 and 2020. Postoperative donor site complications and rates of hernia recurrence were compared between patients with different biologic mesh types.Abdominal complications occurred in 47.1% of patients with NC-PADM, 52.9% of patients with C-PADM, 16.7% of patients with RBOR, and 43.2% of patients with BADM (Our data indicate that RBOR decreases abdominal complications and recurrence rates after ventral hernia repair compared with NC-PADM, C-PADM, and BADM.

BACKGROUND Reinforcement of the abdominal wall with synthetic mesh in autologous breast reconstruction using abdominal free tissue transfer decreases the risk of bulging and herniation. However, the impact of the plane of mesh placement on donor site complications has not yet been investigated. METHODS We performed a retrospective analysis of 312 patients who had undergone autologous breast reconstruction with muscle-sparing transverse rectus abdominis myocutaneous (MS-TRAM) flaps or deep inferior epigastric perforator (DIEP) flaps as well as polypropylene mesh implantation at the donor site. Donor site complications were compared among patients with different flap types and different mesh positions including overlay (n = 90), inlay and overlay (I-O; n = 134), and sublay (n = 88). RESULTS Abdominal hernias occurred in 2.86% of patients who had undergone MS-TRAM reconstructions and in 2.63% of patients who had undergone DIEP reconstructions. When comparing patients with different mesh positions, donor site complications occurred in 14.4% of patients with overlay mesh, 13.4% of patients with I-O mesh, and 10.2% of patients with sublay mesh (P = 0.68). Abdominal hernias occurred in 4.44% of patients with overlay mesh, 2.24% of patients with I-O mesh, and 2.27% of patients with sublay mesh (P = 0.69). Multivariable logistic regression analysis did not identify a significant association between mesh position and hernia rates as well as wound complications. CONCLUSIONS Our data indicate that the plane of synthetic mesh placement in relation to the rectus abdominis muscle does not impact the rate of postoperative donor site complications in patients undergoing breast reconstruction with MS-TRAM or DIEP flaps.

Tissue repair and healing remain among the most complicated processes that occur during postnatal life. Humans and other large organisms heal by forming fibrotic scar tissue with diminished function, while smaller organisms respond with scarless tissue regeneration and functional restoration. Well-established scaling principles reveal that organism size exponentially correlates with peak tissue forces during movement, and evolutionary responses have compensated by strengthening organ-level mechanical properties. How these adaptations may affect tissue injury has not been previously examined in large animals and humans. Here, we show that blocking mechanotransduction signaling through the focal adhesion kinase pathway in large animals significantly accelerates wound healing and enhances regeneration of skin with secondary structures such as hair follicles. In human cells, we demonstrate that mechanical forces shift fibroblasts toward pro-fibrotic phenotypes driven by ERK-YAP activation, leading to myofibroblast differentiation and excessive collagen production. Disruption of mechanical signaling specifically abrogates these responses and instead promotes regenerative fibroblast clusters characterized by AKT-EGR1., Humans and other large mammals heal wounds by forming fibrotic scar tissue with diminished function. Here, the authors show that disrupting mechanotransduction through the focal adhesion kinase pathway in large animals accelerates healing, prevents fibrosis, and enhances skin regeneration.

The outbreak of COVID-19 has created an unprecedent global crisis. While the polymerase chain reaction (PCR) is the gold standard method for detecting active SARS-CoV-2 infection, alternative high-throughput diagnostic tests are of a significant value to meet universal testing demands. Here, we describe a new design of the MasSpec Pen technology integrated to electrospray ionization (ESI) for direct analysis of clinical swabs and investigate its use for COVID-19 screening. The redesigned MasSpec Pen system incorporates a disposable sampling device refined for uniform and efficient analysis of swab tips via liquid extraction directly coupled to an ESI source. Using this system, we analyzed nasopharyngeal swabs from 244 individuals including symptomatic COVID-19 positive, symptomatic negative, and asymptomatic negative individuals, enabling rapid detection of rich lipid profiles. Two statistical classifiers were generated based on the lipid information acquired. Classifier 1 was built to distinguish symptomatic PCR-positive from asymptomatic PCR-negative individuals, yielding a cross-validation accuracy of 83.5%, sensitivity of 76.6%, and specificity of 86.6%, and validation set accuracy of 89.6%, sensitivity of 100%, and specificity of 85.3%. Classifier 2 was built to distinguish symptomatic PCR-positive patients from negative individuals including symptomatic PCR-negative patients with moderate to severe symptoms and asymptomatic individuals, yielding a cross-validation accuracy of 78.4%, specificity of 77.21%, and sensitivity of 81.8%. Collectively, this study suggests that the lipid profiles detected directly from nasopharyngeal swabs using MasSpec Pen-ESI mass spectrometry (MS) allow fast (under a minute) screening of the COVID-19 disease using minimal operating steps and no specialized reagents, thus representing a promising alternative high-throughput method for screening of COVID-19.

BACKGROUND Accurate tissue diagnosis during ovarian cancer surgery is critical to maximize cancer excision and define treatment options. Yet, current methods for intraoperative tissue evaluation can be time intensive and subjective. We have developed a handheld and biocompatible device coupled to a mass spectrometer, the MasSpec Pen, which uses a discrete water droplet for molecular extraction and rapid tissue diagnosis. Here we evaluated the performance of this technology for ovarian cancer diagnosis across different sample sets, tissue types, and mass spectrometry systems. METHODS MasSpec Pen analyses were performed on 192 ovarian, fallopian tube, and peritoneum tissue samples. Samples were evaluated by expert pathologists to confirm diagnosis. Performance using an Orbitrap and a linear ion trap mass spectrometer was tested. Statistical models were generated using machine learning and evaluated using validation and test sets. RESULTS High performance for high-grade serous carcinoma (n = 131; clinical sensitivity, 96.7%; specificity, 95.7%) and overall cancer (n = 138; clinical sensitivity, 94.0%; specificity, 94.4%) diagnoses was achieved using Orbitrap data. Variations in the mass spectra from normal tissue, low-grade, and high-grade serous ovarian cancers were observed. Discrimination between cancer and fallopian tube or peritoneum tissues was also achieved with accuracies of 92.6% and 87.9%, respectively, and 100% clinical specificity for both. Using ion trap data, excellent results for high-grade serous cancer vs normal ovarian differentiation (n = 40; clinical sensitivity, 100%; specificity, 100%) were obtained. CONCLUSIONS The MasSpec Pen, together with machine learning, provides robust molecular models for ovarian serous cancer prediction and thus has potential for clinical use for rapid and accurate ovarian cancer diagnosis.

Intraoperative delineation of tumor margins is critical for effective pancreatic cancer surgery. Yet, intraoperative frozen section analysis of tumor margins is a time-consuming and often challenging procedure that can yield confounding results due to histologic heterogeneity and tissue-processing artifacts. We have previously described the development of the MasSpec Pen technology as a handheld mass spectrometry–based device for nondestructive tissue analysis. Here, we evaluated the usefulness of the MasSpec Pen for intraoperative diagnosis of pancreatic ductal adenocarcinoma based on alterations in the metabolite and lipid profiles in in vivo and ex vivo tissues. We used the MasSpec Pen to analyze 157 banked human tissues, including pancreatic ductal adenocarcinoma, pancreatic, and bile duct tissues. Classification models generated from the molecular data yielded an overall agreement with pathology of 91.5%, sensitivity of 95.5%, and specificity of 89.7% for discriminating normal pancreas from cancer. We built a second classifier to distinguish bile duct from pancreatic cancer, achieving an overall accuracy of 95%, sensitivity of 92%, and specificity of 100%. We then translated the MasSpec Pen to the operative room and predicted on in vivo and ex vivo data acquired during 18 pancreatic surgeries, achieving 93.8% overall agreement with final postoperative pathology reports. Notably, when integrating banked tissue data with intraoperative data, an improved agreement of 100% was achieved. The result obtained demonstrate that the MasSpec Pen provides high predictive performance for tissue diagnosis and compatibility for intraoperative use, suggesting that the technology may be useful to guide surgical decision-making during pancreatic cancer surgeries.

The outbreak of COVID-19 has created an unprecedent global crisis. While PCR is the gold standard method for detecting active SARS-CoV-2 infection, alternative high-throughput diagnostic tests are of significant value to meet universal testing demands. Here, we describe a new design of the MasSpec Pen technology integrated to electrospray ionization (ESI) for direct analysis of clinical swabs and investigate its use for COVID-19 screening. The redesigned MasSpec Pen system incorporates a disposable sampling device refined for uniform and efficient analysis of swab tips via liquid extraction directly coupled to a ESI source. Using this system, we analyzed nasopharyngeal swabs from 244 individuals including symptomatic COVID-19 positive, symptomatic negative, and asymptomatic negative individuals, enabling rapid detection of rich lipid profiles. Two statistical classifiers were generated based on the lipid information aquired. Classifier 1 was built to distinguish symptomatic PCR-positive from asymptomatic PCR-negative individuals, yielding cross-validation accuracy of 83.5%, sensitivity of 76.6%, and specificity of 86.6%, and validation set accuracy of 89.6%, sensitivity of 100%, and specificity of 85.3%. Classifier 2 was built to distinguish symptomatic PCR-positive patients from negative individuals including symptomatic PCR-negative patients with moderate to severe symptoms and asymptomatic individuals, yielding a cross-validation accuracy of 78.4% accuracy, specificity of 77.21%, and sensitivity of 81.8%. Collectively, this study suggests that the lipid profiles detected directly from nasopharyngeal swabs using MasSpec Pen-ESI MS allows fast (under a minute) screening of COVID-19 disease using minimal operating steps and no specialized reagents, thus representing a promising alternative high-throughput method for screening of COVID-19.

Background Clinical trials report occurrence of non-melanoma skin cancers (NMSC) with ruxolitinib in polycythemia (PV) or myelofibrosis (MF) patients, however the level of risk and effect of covariates are not known in the real-world setting. Objective To systematically assess the risk of developing non-melanoma skin cancer (NMSC) after ruxolitinib exposure in PV or MF patients. Methods A 10-year retrospective cohort of PV or MF patients at Stanford Medical Center was identified and matched on age, gender, race, Charlson comorbidity index, disease diagnosis, and follow-up time. The main outcome measure was Hazard Ratio (HR) for NMSC (comprised of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC)) after ruxolitinib exposure, adjusted for covariates. Results The study cohort consisted of 564 patients (188 exposed to ruxolitinib for at least 4 weeks, 376 unexposed). Ruxolitinib-exposed PV or MF patients had an adjusted NMSC HR of 2.69 (95% Confidence Interval (CI), 1.03-7.02). In particular, ruxolitinib exposure was associated with SCC, HR=3.24 (95% CI, 1.45-7.22), with non-JAK2 mutated patients showing even higher SCC risk, HR=7.40 (2.54-21.63). Limitations Retrospective design. Conclusions and Relevance Our real-world results indicate that SCC risk is increased in PV or MF patients taking ruxolitinib and supports consideration of skin cancer monitoring.

Skin allo- and xenotransplantation are the standard treatment for major burns when donor sites for autografts are not available and have been shown to significantly accelerate wound healing. Although the cellular elements of foreign grafts are rejected, the extracellular matrix components integrate into the wound and may underlie their beneficial effects on wound healing. The molecular mechanisms defining the relationship between the immune response to foreign grafts and their impact on wound healing have not been fully elucidated. Here, we investigated changes in collagen architecture after xenogeneic implantation of clinically available human biologic scaffolds. We show that collagen deposition in response to the implantation of human split-thickness skin grafts (hSTSG) containing live cells recapitulates normal skin architecture, whereas human acellular dermal matrix (ADM) grafts led to highly aligned collagen deposition, characteristic of fibrosis and scar. Using single-cell RNA-sequencing, we show that macrophage differentiation in response to hSTSG is driven by vitamin D (VD) signaling toward Trem2+ subpopulations with an enrichment of pro-angiogenic and anti-fibrotic transcriptomic programs. We subsequently induced this regenerative subpopulation in vitro by treating bone marrow-derived cells with vitamin D3 and found that hydrogel delivery of Trem2+ macrophages significantly accelerated wound closure in a human-like murine excisional wound model. Our study identifies the preclinical therapeutic potential of Trem2+ macrophages to mitigate fibrosis and promote wound healing and provides a novel effective strategy to develop advanced cell therapies for complex wounds.One Sentence SummaryVitamin D-activated Trem2+ macrophages promote angiogenesis and mitigate fibrosis, providing a novel effective strategy to develop advanced cell therapies for complex wounds.

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative, raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 seconds per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Metabolic predictors of meat type selected included several metabolites previously described reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is as a promising alternative analytical method for the investigation of meat fraud.

The Roma population suffers from severe poverty, social exclusion, and some of the worst health conditions in the industrialized world. Herein, we report on cardiovascular disease (CVD) risk factors in the Ukrainian Roma and present a meta-analysis of the prevalence of CVD risk factors in 16 Roma populations worldwide. The meta-analyses of CVD risk factors in Roma (n = 16,552) vs. non-Roma majority population of the same country (n = 127,874) included publicly available data. Ukrainian field survey included 339 adults of both sexes and outcomes of interest were hypertension, body mass index (BMI), smoking, education, and employment status. Furthermore, 35.7% of the Ukrainian Roma were hypertensive, 69.3% unemployed, and 48.4% never went to school. Ukrainian Roma women were more likely to be underweight and more prone to be hypertensive, with odds of hypertension increasing with age, BMI, and positive smoking status. Meta-analyses showed that, in comparison with non-Roma worldwide, the Roma bear significantly higher risk factor loads related to smoking (OR = 2.850), diabetes (OR = 1.433), abdominal obesity (OR = 1.276), and metabolic syndrome (OR = 1.975), with lower loads for hypertension (OR = 0.607) and BMI ≥ 25 kg/m2 (OR = 0.872). To conclude, the CVD risk factors which are more common in Roma than in the majority population may reflect their poor health-related behaviors and inadequate access to health education.

Intraoperative tissue analysis is critical to guide surgical procedures and improve patient outcomes. Here, we describe the clinical translation and intraoperative use of the MasSpec Pen technology for direct molecular analysis of in vivo and freshly excised tissues in the operating room. In this study, the MasSpec Pen was used by surgeons and surgical staff during 100 surgeries over a 12-month period, allowing rapid detection of rich mass spectral profiles from 715 in vivo and ex vivo analyses performed on thyroid, parathyroid, lymph node, breast, pancreatic, and bile duct tissues during parathyroidectomies, thyroidectomies, breast, and pancreatic neoplasia surgeries. The MasSpec Pen enabled gentle extraction and sensitive detection of various molecular species including small metabolites and lipids using a droplet of sterile water without causing apparent tissue damage. Notably, effective molecular analysis was achieved while no limitations to sequential histologic tissue analysis were identified and no device-related complications were reported for any of the patients. Collectively, this study shows that the MasSpec Pen system can be successfully incorporated into the operating room, allowing direct detection of rich molecular profiles from tissues with a seconds-long turnaround time that could be inform surgical and clinical decisions without disrupting tissue analysis workflows.

Plasma and tissue from breast cancer patients are valuable for diagnostic/prognostic purposes and are accessible by multiple mass spectrometry (MS) tools. Liquid chromatography-mass spectrometry (LC-MS) and ambient mass spectrometry imaging (MSI) were shown to be robust and reproducible technologies for breast cancer diagnosis. Here, we investigated whether there is a correspondence between lipid cancer features observed by desorption electrospray ionization (DESI)-MSI in tissue and those detected by LC-MS in plasma samples. The study included 28 tissues and 20 plasma samples from 24 women with ductal breast carcinomas of both special and no special type (NST) along with 22 plasma samples from healthy women. The comparison of plasma and tissue lipid signatures revealed that each one of the studied matrices (i.e., blood or tumor) has its own specific molecular signature and the full interposition of their discriminant ions is not possible. This comparison also revealed that the molecular indicators of tissue injury, characteristic of the breast cancer tissue profile obtained by DESI-MSI, do not persist as cancer discriminators in peripheral blood even though some of them could be found in plasma samples.

Thyroid neoplasia is common and requires appropriate clinical workup with imaging and fine-needle aspiration (FNA) biopsy to evaluate for cancer. Yet, up to 20% of thyroid nodule FNA biopsies will be indeterminate in diagnosis based on cytological evaluation. Genomic approaches to characterize the malignant potential of nodules showed initial promise but have provided only modest improvement in diagnosis. Here, we describe a method using metabolic analysis by desorption electrospray ionization mass spectrometry (DESI-MS) imaging for direct analysis and diagnosis of follicular cell-derived neoplasia tissues and FNA biopsies. DESI-MS was used to analyze 178 tissue samples to determine the molecular signatures of normal, benign follicular adenoma (FTA), and malignant follicular carcinoma (FTC) and papillary carcinoma (PTC) thyroid tissues. Statistical classifiers, including benign thyroid versus PTC and benign thyroid versus FTC, were built and validated with 114,125 mass spectra, with accuracy assessed in correlation with clinical pathology. Clinical FNA smears were prospectively collected and analyzed using DESI-MS imaging, and the performance of the statistical classifiers was tested with 69 prospectively collected clinical FNA smears. High performance was achieved for both models when predicting on the FNA test set, which included 24 nodules with indeterminate preoperative cytology, with accuracies of 93% and 89%. Our results strongly suggest that DESI-MS imaging is a valuable technology for identification of malignant potential of thyroid nodules.

The histological and molecular subtypes of breast cancer demand distinct therapeutic approaches. Invasive ductal carcinoma (IDC) is subtyped according to estrogen-receptor (ER), progesterone-receptor (PR), and HER2 status, among other markers. Desorption-electrospray-ionization-mass-spectrometry imaging (DESI-MSI) is an ambient-ionization MS technique that has been previously used to diagnose IDC. Aiming to investigate the robustness of ambient-ionization MS for IDC diagnosis and subtyping over diverse patient populations and interlaboratory use, we report a multicenter study using DESI-MSI to analyze samples from 103 patients independently analyzed in the United States and Brazil. The lipid profiles of IDC and normal breast tissues were consistent across different patient races and were unrelated to country of sample collection. Similar experimental parameters used in both laboratories yielded consistent mass-spectral data in mass-to-charge ratios ( m/ z) above 700, where complex lipids are observed. Statistical classifiers built using data acquired in the United States yielded 97.6% sensitivity, 96.7% specificity, and 97.6% accuracy for cancer diagnosis. Equivalent performance was observed for the intralaboratory validation set (99.2% accuracy) and, most remarkably, for the interlaboratory validation set independently acquired in Brazil (95.3% accuracy). Separate classification models built for ER and PR statuses as well as the status of their combined hormone receptor (HR) provided predictive accuracies (89.0%), although low classification accuracies were achieved for HER2 status. Altogether, our multicenter study demonstrates that DESI-MSI is a robust and reproducible technology for rapid breast-cancer-tissue diagnosis and therefore is of value for clinical use.

Desorption electrospray ionization (DESI) mass spectrometry imaging has become a powerful strategy for analysis of tissue sections, enabling differentiation of normal and diseased tissue based on changes in the lipid profiles. The most common DESI workflow involves collection of MS1 spectra as the DESI spray is rastered over a tissue section. Relying on MS1 spectra inherently limits the ability to differentiate isobaric and isomeric species or evaluate variations in the relative abundances of key isomeric lipids, such as double-bond positional isomers which may distinguish normal and diseased tissues. Here, 193 nm ultraviolet photodissociation (UVPD), a technique capable of differentiating double-bond positional isomers, is coupled with DESI to map differences in the double-bond isomer composition in tissue sections in a fast, high throughput manner compatible with imaging applications.

Precise diagnosis and subtyping of kidney tumors are imperative to optimize and personalize treatment decision for patients. Patients with the most common benign renal tumor, renal oncocytomas, may be overtreated with surgical resection because of limited preoperative diagnostic methods that can accurately identify the benign condition with certainty. In this study, desorption electrospray ionization (DESI)-mass spectrometry (MS) imaging was applied to study the metabolic and lipid profiles of various types of renal tissues, including normal kidney, renal oncocytoma, and renal cell carcinomas (RCC). A total of 73,992 mass spectra from 71 patient samples were obtained and used to build predictive models using the least absolute shrinkage and selection operator (Lasso). Overall accuracies of 99.47% per pixel and 100% per patient for prediction of the three tissue types were achieved. In particular, renal oncocytoma and chromophobe RCC, which present the most significant morphologic overlap and are sometimes indistinguishable using histology alone, were also investigated and the predictive models built yielded 100% accuracy in discriminating these tumor types. Discrimination of three subtypes of RCC was also achieved on the basis of DESI-MS imaging data. Importantly, several small metabolites and lipids species were identified as characteristic of individual tissue types and chemically characterized using tandem MS and high mass accuracy measurements. Collectively, our study shows that the metabolic data acquired by DESI-MS imaging in conjunction with statistical modeling allows discrimination of renal tumors and thus has the potential to be used in the clinical setting to improve treatment of patients with kidney tumor. Significance: Metabolic data acquired by mass spectrometry imaging in conjunction with statistical modeling allows discrimination of renal tumors and has the potential to be used in the clinic to improve treatment of patients.

Precise removal of pancreatic ductal adenocarcinoma (PDAC) with microscopically negative margins, commonly assessed by frozen section analysis, is associated with longer disease-free survival. However, histologic complexities and tissue-processing artifacts can render frozen section analysis of PDAC margins a challenging and time-consuming task, with reported accuracies dependent on the skillset and subspecialty of the pathologist on call. We developed the MasSpec Pen, a handheld device coupled to a mass spectrometer, for rapid (~15 s) and nondestructive molecular analysis and diagnosis of tissues. The MasSpec Pen supplies a discrete water droplet onto a tissue's surface, allowing diagnostic metabolites and lipids to be extracted into the droplet and then transmitted into a mass spectrometer for analysis. Here, we evaluate the performance of the MasSpec Pen for intraoperative diagnosis of PDAC in human pancreatic and bile duct margins. Pancreatic and bile duct tissue samples (N=157) were obtained from the Cooperative Human Tissue Network and Baylor College of Medicine and stored at -80°C prior to analysis. A Q Exactive mass spectrometer (Thermo Scientific) coupled to the MasSpec Pen was used for analysis of thawed samples in the negative ion mode. Tissues were then cryo-sectioned, H&E stained, and blindly evaluated by a pathologist. Based on the distinct molecular profiles acquired, we generated two statistical classifiers using lasso penalized logistic regression for distinguishing PDAC from healthy pancreas and bile duct tissue based on a sparse set of molecular features indicative of disease state. For distinguishing normal pancreas from PDAC, an overall accuracy of 91.5%, sensitivity of 95.5%, and specificity of 89.7% was achieved for training, validation, and test sets. Classification results for discriminating normal bile duct from PDAC had an overall accuracy of 95%, sensitivity of 92%, and specificity of 100% in training and validation. We have begun clinical testing of the MasSpec Pen in human surgeries following its successful translation to an operating room at Texas Medical Center. To date, the MasSpec Pen has been used to analyze in vivo and fresh ex vivo tissue in 19 pancreatic surgeries. When predicting on 64 intraoperative analyses using classification models built on banked data, 93.8% agreement with final postoperative pathology reports was achieved. While further validation studies are needed, our results show that the MasSpec Pen can distinguish PDAC from normal pancreas and bile duct tissues with high accuracy and is compatible for in vivo use, suggesting this technology may be valuable for near real-time margin evaluation during pancreatic oncologic surgeries. Citation Format: Mary E. King, Jialing Zhang, John Q. Lin, Kyana Y. Garza, Rachel J. DeHoog, Clara L. Feider, Alena V. Bensussan, Marta Sans, Anna Krieger, Sunil Badal, Michael F. Keating, Sadhna Dhingra, Wendong Yu, George Van Buren, Christopher Pirko, Kirtan Brahmbhatt, William E. Fisher, James W. Suliburk, Livia S. Eberlin. Clinical evaluation of the MasSpec Pen technology for rapid diagnosis and margin assessment in pancreatic cancer surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 624.

Introduction: The highest concentration of military personnel in the United States is located in Hawaii where occupational exposures, such as to asbestos in the Pacific Fleet shipyards, predispose them to thoracic malignancies. For this reason, Veterans Affairs (VA) insurance outcomes for lung cancer in Hawaii are of interest. Methods: All cases of lung cancer in the Hawaii Tumor Registry from 2000 to 2015 were evaluated. The selection criterion included evidence of extensive-stage SCLC (ES-SCLC) or metastatic NSCLC. Overall survival was compared using the Kaplan-Meier log-rank method. Univariate analysis and multivariable analysis (MVA) were carried out to understand the variables associated with overall survival. Results: There were 434 cases of ES-SCLC and 2139 cases of metastatic NSCLC identified. VA insurance (median survival [MS], 2 mo), Medicaid (MS, 4 mo), and Medicare (MS, 4 mo) had worse survival (log-rank p < 0.001) than private insurance (MS, 8 mo). In ES-SCLC, VA insurance (hazard ratio [HR], 2.74; 95% confidence interval [CI]: 1.50–5.01; p = 0.001) and Medicaid (HR, 1.46; 95% CI: 1.04–2.03; p = 0.027) had significantly worse survival compared with private insurance on MVA. VA insurance (HR, 1.84; 95% CI: 1.34–2.53; p < 0.001) and Medicaid (HR, 1.40; 95% CI: 1.20–1.63; p < 0.001) also had worse survival compared with private insurance in metastatic NSCLC on MVA. Conclusions: VA insurance coverage was associated with dismal survival for metastatic lung cancer that was effectively similar to hospice or supportive care, compelling further investigation to identify reasons for this disparity.

Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.

Oncocytic tumors are characterized by an excessive eosinophilic, granular cytoplasm due to aberrant accumulation of mitochondria. Mutations in mitochondrial DNA occur in oncocytic thyroid tumors, but there is no information about their lipid composition, which might reveal candidate theranostic molecules. Here, we used desorption electrospray ionization mass spectrometry (DESI-MS) to image and chemically characterize the lipid composition of oncocytic thyroid tumors, as compared with nononcocytic thyroid tumors and normal thyroid samples. We identified a novel molecular signature of oncocytic tumors characterized by an abnormally high abundance and chemical diversity of cardiolipins (CL), including many oxidized species. DESI-MS imaging and IHC experiments confirmed that the spatial distribution of CLs overlapped with regions of accumulation of mitochondria-rich oncocytic cells. Fluorescent imaging and mitochondrial isolation showed that both mitochondrial accumulation and alteration in CL composition of mitochondria occurred in oncocytic tumors cells, thus contributing the aberrant molecular signatures detected. A total of 219 molecular ions, including CLs, other glycerophospholipids, fatty acids, and metabolites, were found at increased or decreased abundance in oncocytic, nononcocytic, or normal thyroid tissues. Our findings suggest new candidate targets for clinical and therapeutic use against oncocytic tumors. Cancer Res; 76(22); 6588–97. ©2016 AACR.

Purpose/Objective(s): Oncogene-addiction or -dependence is a biological phenomenon whereby tumors following oncogene-inactivation exhibit dramatic regression revealing tumor cells that are dependent on their initiating oncogene for survival. This phenomenon has become more widely appreciated clinically with the emergence of oncogene targeted therapies that expose a subset of human malignancies with this phenotype. A human example are "oncogene-addicted" patients with EGFR-mutated bronchioloalveolar carcinomas (BACs). A critical question is the identification of patients who most benefit from these targeted therapies. Novel methods for determining and predicting treatment response are therefore needed. The Myc and Ras oncogenes have pleiotropic effects on cell autonomous functions such as proliferation, apoptosis and DNA damage repair and cell non-autonomous functions such as angiogenesis, the sum of which can drive the process of oncogenesis. The murine counterpart to "oncogene-addicted" human BACs are Ras-induced "oncogene-addicted" non-small cell lung cancers (NSCLCs). Corroborating this supposition are human mutational studies that suggest Ras and EGFR mutations are mutually exclusive in NSCLC. Materials/Methods: We constructed mouse preclinical lung cancer model systems to address these issues. Using a conditional lung specific gene expression system we analyzed transgenic mouse models of Myc, Ras or Myc/Ras induced lung adenocarcinoma. Results: These transgenic mice develop primary lung adenocarcinomas with variable latency (26-51 weeks) and clinical presentation that is dependent on their genotype. Upon oncogene-inactivation in these murine models, we have found that Ras, but not Myc induced lung adenocarcinomas regress in a matter of weeks completely. We measured quantitatively the clinical behavior of murine lung tumors in situ after oncogene-inactivation by use of serial micro-computed tomography (microCT) imaging. By modeling the regression curves of each transgenic system, we were able to express the difference mathematically between the tumor regression of Rasand Myc-induced tumors. The modeling also allowed us to distinguish that double mutant, Ras/Myc-induced tumors, were likely composed of two dominant populations with behavior similar to single Rasand Myc-induced tumors. We then used our data array as a training set for a predictive support vector machine algorithm which is highly accurate at predicting the regression of murine tumors based on only three serial weekly microCT scans at the initiation of oncogeneinactivation. Conclusions: Our work incorporates highly penetrant spontaneously arising murine lung tumor models, non-invasive serial tumor imaging and predictive mathematically modeling. This system serves as a more clinically relevant bridge for studies transitioning from the bench to the clinic and can also be used to probe basic questions of oncogene-addiction. Furthermore, these preclinical studies suggest a novel method for predicting tumor responses in human BACs.