This dataset contains Cancer Incidence data for Prostate Cancer(All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are for males segmented age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

IntroductionSociodemographic disparities in genitourinary cancer-related mortality have been insufficiently studied, particularly across multiple cancer types. This study aimed to investigate gender, racial, and geographic disparities in mortality rates for the most common genitourinary cancers in the United States.MethodsMortality data for prostate, bladder, kidney, and testicular cancers were obtained from the Centers for Disease Control and Prevention (CDC) WONDER database between 1999 and 2020. Age-adjusted mortality rates (AAMRs) were analyzed by year, gender, race, urban–rural status, and geographic region using a significance level of p < 0.05.ResultsOverall, AAMRs for prostate, bladder, and kidney cancer declined significantly, while testicular cancer-related mortality remained stable. Bladder and kidney cancer AAMRs were 3–4 times higher in males than females. Prostate cancer mortality was highest in black individuals/African Americans and began increasing after 2015. Bladder cancer mortality decreased significantly in White individuals, Black individuals, African Americans, and Asians/Pacific Islanders but remained stable in American Indian/Alaska Natives. Kidney cancer-related mortality was highest in White individuals but declined significantly in other races. Testicular cancer mortality increased significantly in White individuals but remained stable in Black individuals and African Americans. Genitourinary cancer mortality decreased in metropolitan areas but either increased (bladder and testicular cancer) or remained stable (kidney cancer) in non-metropolitan areas. Prostate and kidney cancer mortality was highest in the Midwest, bladder cancer in the South, and testicular cancer in the West.DiscussionSignificant sociodemographic disparities exist in the mortality trends of genitourinary cancers in the United States. These findings highlight the need for targeted interventions and further research to address these disparities and improve outcomes for all populations affected by genitourinary cancers.

Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFκB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members' biomolecular activities, the current list of pathway members and systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFkB pathway members. Ahe newly predicted interactions between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9's potential biological role in prostate cancer cell growth regulation. We combined 653 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFkB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFkB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies. All supplementary figures, tables, input data, and source code for analysis are available at http://huttenhower.sph.harvard.edu/cap

Castration-resistant prostate cancer (CRPC) is associated with resistance to androgen deprivation therapy, and an increase in the population of neuroendocrine (NE) differentiated cells. It is hypothesized that NE differentiated cells secrete neuropeptides that support androgen-independent tumor growth and induce aggressiveness of adjacent proliferating tumor cells through a paracrine mechanism. The cytochrome b561 (CYB561) gene, which codes for a secretory vesicle transmembrane protein, is constitutively expressed in NE cells and highly expressed in CRPC. CYB561 is involved in the α-amidation-dependent activation of neuropeptides and contributes to regulating iron metabolism which is often dysregulated in cancer. These findings led us to hypothesize that CYB561 may be a key player in the NE differentiation process that drives the progression and maintenance of the highly aggressive NE phenotype in CRPC. In our study, we found that CYB561 expression is upregulated in metastatic and NE prostate cancer (NEPC) tumors and cell lines compared to normal prostate epithelia and that its expression is independent of androgen regulation. Knockdown of CYB561 in androgen-deprived LNCaP cells dampened NE differentiation potential and transdifferentiation-induced increase in iron levels. In NEPC PC-3 cells, depletion of CYB561 reduced the secretion of growth-promoting factors, lowered intracellular ferrous iron concentration, and mitigated the highly aggressive nature of these cells in complementary assays for cancer hallmarks. These findings demonstrate the role of CYB561 in facilitating transdifferentiation and maintenance of NE phenotype in CRPC through its involvement in neuropeptide biosynthesis and iron metabolism pathways. Methods Protein expression data was evaluated using a western blot. In silico analysis of gene expression data was performed by examining the Bittner Multi-cancer clinical microarray data set (GSE2109) from the International Genomics Consortium Project for Oncology (www.intgen.org) for neuropeptide receptor mRNA expression across different clinical tumor types. Gene expression analysis was performed by reverse transcription-quantitative PCR (RT-qPCR). Data for gene expression analysis (normalized to 18s rRNA, GAPDH, or β-Actin (ACTB) transcript levels) were log10 transformed before statistical analysis. The basal and androgen-regulated gene expression data were analyzed using one-way ANOVA followed by Tukey’s post hoc test. Results from the transdifferentiation experiment were analyzed using two-way ANOVA to determine the main effects of CYB561 knockdown and transdifferentiation, after which Student’s unpaired t-test was done to determine the effect of transdifferentiation within an shRNA group and the effect of CYB561 knockdown in cells maintained in the same growth condition. Data from the LNCaP hormone treatment and starvation gene expression analysis were analyzed using the Student’s unpaired t-test. All statistical analyses were done using GraphPad Prism version 8.0 (GraphPad Software, La Jolla California USA, www.graphpad.com), and P < 0.05 was accepted as statistically significant.

Data Images are not in dcm format, the images are in jpg or png to fit the model Data contain 3 chest cancer types which are Adenocarcinoma,Large cell carcinoma, Squamous cell carcinoma , and 1 folder for the normal cell Data folder is the main folder that contain all the step folders inside Data folder are test , train , valid

test represent testing set train represent training set valid represent validation set training set is 70% testing set is 20% validation set is 10%

Adenocarcinoma Adenocarcinoma of the lung: Lung adenocarcinoma is the most common form of lung cancer accounting for 30 percent of all cases overall and about 40 percent of all non-small cell lung cancer occurrences. Adenocarcinomas are found in several common cancers, including breast, prostate and colorectal. Adenocarcinomas of the lung are found in the outer region of the lung in glands that secrete mucus and help us breathe. Symptoms include coughing, hoarseness, weight loss and weakness.

Large cell carcinoma Large-cell undifferentiated carcinoma: Large-cell undifferentiated carcinoma lung cancer grows and spreads quickly and can be found anywhere in the lung. This type of lung cancer usually accounts for 10 to 15 percent of all cases of NSCLC. Large-cell undifferentiated carcinoma tends to grow and spread quickly. ** Squamous cell carcinoma** Squamous cell: This type of lung cancer is found centrally in the lung, where the larger bronchi join the trachea to the lung, or in one of the main airway branches. Squamous cell lung cancer is responsible for about 30 percent of all non-small cell lung cancers, and is generally linked to smoking.

And the last folder is the normal CT-Scan images

Acknowledgements We wouldn't be here without the help of others and the resources we found. thanks for all of my team and the people who supported us

Inspiration I want to hear all your feedback

Radium-223 (Ra-223) received U.S. Food and Drug Administration (FDA) approval for treating castration-resistant prostate cancer with symptomatic bone metastases, excluding visceral metastases. Despite this, the safety profile of Ra-223 in large-scale, population-based use still needs to be explored. This research assesses the side effects of Ra-223 by analyzing reports of adverse events (AEs) from the FDA’s Adverse Event Reporting System (FAERS) database. Four sequential analysis strategies were employed to assess the significance of these AEs. In total, 4,228 Ra-223-related AE reports were identified in the FAERS database. These Ra-223-induced AEs were observed in 26 target system organ classes (SOCs). 124 Ra-223-induced AEs were detected in 26 SOCs, predominantly affecting the blood and lymphatic systems. Other notable AEs included diarrhea, nausea, asthenia, fatigue, malaise, and decreased appetite, some of which were not previously documented in product specifications. The median time to onset of AEs was 56 days (Interquartile Range 26–103 days), with the majority of AEs occurring within the first three months after Ra-223 administration. Our findings align with clinical observations and suggest potential new and unexpected AEs related to Ra-223, underscoring the need for prospective clinical studies to confirm these results and clarify their relationships. These insights provide valuable evidence for further safety studies and the rational use of Ra-223.