Mobile phone based mini-spectrometer for rapid screening of skin cancer

We demonstrate a highly sensitive mobile phone based spectrometer that has potential to detect cancerous skin lesions in a rapid, non-invasive manner. Earlier reports of low cost spectrometers utilize the camera of the mobile phone to image the field after moving through a diffraction grating. These approaches are inherently limited by the closed nature of mobile phone image sensors and built in optical elements. The system presented uses a novel integrated grating and sensor that is compact, accurate and calibrated. Resolutions of about 10 nm can be achieved. Additionally, UV and visible LED excitation sources are built into the device. Data collection and analysis is simplified using the wireless interfaces and logical control on the smart phone. Furthermore, by utilizing an external sensor, the mobile phone camera can be used in conjunction with spectral measurements. We are exploring ways to use this device to measure endogenous fluorescence of skin in order to distinguish cancerous from non-cancerous lesions with a mobile phone based dermatoscope

Multiomic immune clockworks of pregnancy

Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy “immune clock” is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Barriers to achieving controlled rheumatoid arthritis in the United Arab Emirates: a cross-sectional study

To better understand the factors that affect low disease activity (DAS28 ≤ 3.2, LDA) in rheumatoid arthritis (RA) and barriers within the UAE, demographic/treatment data and DAS28 scores were collected through chart reviews of 182 consecutive RA patients seen at a private clinic in Dubai over a 2-month period. Patients were separated into a LDA group and a group comprised of moderate (3.2 < DAS28 < 5.1) or high disease activity (DAS28 ≥ 5.1) (MHDA). We then examined variables that may be associated with LDA and re-examined the MHDA group for barriers. While 97 (53 %) of the 182 patients had achieved the treatment target of DAS28 ≤ 3.2, 85 (47 %) had MHDA. A significantly larger portion of LDA patients had been previously treated with sulfasalazine (36 in LDA vs. 14 in MHDA, P = 0.002) or was presently on biological treatments (24 vs. 9, P = 0.013). For the 85 MHDA patients, 40 (22 % of 182) exhibited resistant disease with 25 (13.7 % of 182) failing their current first tier disease-modifying anti-rheumatic drug (DMARD) treatment or combinations and 15 (8.2 % of 182) failing current anti-TNF or biologic treatment. Reasons listed were primarily socioeconomic with 40 % of the resistant disease group unable to afford biologicals and 52 % of the patient-driven preference group discontinuing DMARDs against professional advice. Going forward, emphasis on the agreement between patient and rheumatologist on treatment, specifically regarding how DMARDs help relieve symptoms and their proper use, could help reduce the percentage of MHDA patients in the UAE

Cell types of origin of the cell-free transcriptome.

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases

Characterization of the expression of the pro-metastatic MenaINV isoform during breast tumor progression

Several functionally distinct isoforms of the actin regulatory Mena are produced by alternative splicing during tumor progression. Forced expression of the Mena[superscript INV] isoform drives invasion, intravasation and metastasis. However, the abundance and distribution of endogenously expressed Mena[superscript INV] within primary tumors during progression remain unknown, as most studies to date have only assessed relative mRNA levels from dissociated tumor samples. We have developed a Mena[superscript INV] isoform-specific monoclonal antibody and used it to examine Mena[superscript INV]expression patterns in mouse mammary and human breast tumors. Mena[superscript INV] expression increases during tumor progression and to examine the relationship between Mena[superscript INV] expression and markers for epithelial or mesenchymal status, stemness, stromal cell types and hypoxic regions. Further, while Mena[superscript INV] robustly expressed in vascularized areas of the tumor, it is not confined to cells adjacent to blood vessels. Altogether, these data demonstrate the specificity and utility of the anti-Mena[superscript INV]-isoform specific antibody, and provide the first description of endogenous Mena[superscript INV]protein expression in mouse and human tumors.United States. Dept. of Defense. Breast Cancer Research Program (Grants W81XWH-10-1-0040 and W81XWH-13-1-0031)National Institutes of Health (U.S.) (Grants U54-CA112967 and GM58801)Massachusetts Institute of Technology. Ludwig Center for Molecular Oncolog

Acidification of tumor at stromal boundaries drives transcriptome alterations associated with aggressive phenotypes

© 2019 American Association for Cancer Research. Acidosis is a fundamental feature of the tumor microenvironment, which directly regulates tumor cell invasion by affecting immune cell function, clonal cell evolution, and drug resistance. Despite the important association of tumor microenvironment acidosis with tumor cell invasion, relatively little is known regarding which areas within a tumor are acidic and how acidosis influences gene expression to promote invasion. Here, we injected a labeled pH-responsive peptide to mark acidic regions within tumors. Surprisingly, acidic regions were not restricted to hypoxic areas and overlapped with highly proliferative, invasive regions at the tumor–stroma interface, which were marked by increased expression of matrix metalloprotei-nases and degradation of the basement membrane. RNA-seq analysis of cells exposed to low pH conditions revealed a general rewiring of the transcriptome that involved RNA splicing and enriched for targets of RNA binding proteins with specificity for AU-rich motifs. Alternative splicing of Mena and CD44, which play important isoform-specific roles in metastasis and drug resistance, respectively, was sensitive to histone acetylation status. Strikingly, this program of alternative splicing was reversed in vitro and in vivo through neutralization experiments that mitigated acidic conditions. These findings highlight a previously underappreciated role for localized acidification of tumor microenvironment in the expression of an alternative splicing-dependent tumor invasion program

Characterization of the expression of the pro-metastatic MenaINV isoform during breast tumor progression

Several functionally distinct isoforms of the actin regulatory Mena are produced by alternative splicing during tumor progression. Forced expression of the Mena[superscript INV] isoform drives invasion, intravasation and metastasis. However, the abundance and distribution of endogenously expressed Mena[superscript INV] within primary tumors during progression remain unknown, as most studies to date have only assessed relative mRNA levels from dissociated tumor samples. We have developed a Mena[superscript INV] isoform-specific monoclonal antibody and used it to examine Mena[superscript INV]expression patterns in mouse mammary and human breast tumors. Mena[superscript INV] expression increases during tumor progression and to examine the relationship between Mena[superscript INV] expression and markers for epithelial or mesenchymal status, stemness, stromal cell types and hypoxic regions. Further, while Mena[superscript INV] robustly expressed in vascularized areas of the tumor, it is not confined to cells adjacent to blood vessels. Altogether, these data demonstrate the specificity and utility of the anti-Mena[superscript INV]-isoform specific antibody, and provide the first description of endogenous Mena[superscript INV]protein expression in mouse and human tumors.United States. Dept. of Defense. Breast Cancer Research Program (Grants W81XWH-10-1-0040 and W81XWH-13-1-0031)National Institutes of Health (U.S.) (Grants U54-CA112967 and GM58801)Massachusetts Institute of Technology. Ludwig Center for Molecular Oncolog

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB