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Background: Only 10-40% of patients with cancer in low-income and middle-income countries were able to access curative or palliative radiotherapy in 2015. We aimed to assess the current status of diagnostic imaging and radiotherapy services in the Baltic countries, eastern Europe, central Asia, and the Caucasus by collecting and analysing local data., Methods: This Access to Radiotherapy (ART) comprehensive analysis used data from 12 countries: the three Baltic countries (Estonia, Latvia, and Lithuania), two countries in eastern Europe (Moldova and Ukraine), four countries in central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan), and three countries in the Caucasus (Armenia, Azerbaijan, and Georgia), referred to here as the ART countries. We were not able to obtain engagement from Turkmenistan. The primary outcome was to update the extent of shortfalls in the availability of diagnostic imaging and radiotherapy technologies and radiotherapy human resources for patients with cancer in former Soviet Union countries. Following the methods of previous similar studies, we developed three questionnaires-targeted towards radiation oncologists, regulatory authorities, and researchers-requesting detailed information on the availability of these resources. Authors from participating countries sent two copies of the appropriate questionnaire to each of 107 identified institutions and coordinated data collection at the national level. Questionnaires were distributed in English and Russian and responses in both languages were accepted. Two virtual meetings held on May 30 and June 1, 2022, were followed by an in-person workshop held in Almaty, Kazakhstan, in September, 2022, attended by representatives from all participating countries, to discuss and further validate the data submitted up to this point. The data were collected on a dedicated web page, developed by the International Cancer Expert Corps, and were then extracted and analysed., Findings: Data were collected between May 10 and Nov 30, 2022. 81 (76%) of the 107 institutions contacted, representing all 12 ART countries, submitted 167 completed questionnaires. The Baltic countries, which are defined as high-income countries, had more diagnostic imaging equipment and radiotherapy human resources (eg, Latvia [1·74] and Lithuania [1·47] have a much higher number of radiation oncologists per 100 000 population than the other ART countries, all of which had <1 radiation oncologist per 100 000 population) and greater radiotherapy technological capacities (higher numbers of linear accelerators and, similar to Georgia, high total external beam radiotherapy capacity) than the other ART countries, as well as high cancer detection rates (Latvia 311 cases per 100 000 population, Lithuania 292, and Estonia 288 vs, for example, 178 in Armenia, 144 in Ukraine, and 72 in Kazakhstan) and low cancer mortality-to-cancer incidence ratios (Estonia 0·43, Latvia 0·49, and Lithuania 0·48; lower than all but Kazakhstan [0·41]). The highest cancer mortality-to-cancer incidence ratios were reported by Moldova (0·71) and Georgia (0·74)., Interpretation: Our findings show that the number of cancer cases, availability of diagnostic imaging equipment, radiation oncologists and radiotherapy capacity, and cancer mortality-to-cancer incidence ratios all vary substantially across the countries studied, with the three high-income, well resourced Baltic countries performing better in all metrics than the included countries in eastern Europe, central Asia, and the Caucasus. These data highlight the challenges faced by many countries in this study, and might help to justify increased investment of financial, human, and technological resources, with the aim to improve cancer treatment outcomes., Funding: US Department of Energy's National Nuclear Security Administration's Office of Radiological Security., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: This study aimed to analyze the association between the behavior of cancer patients, measured using passively and continuously generated data streams from smartphone sensors (as in digital phenotyping), and perceived fear of COVID-19 and COVID-19 vaccination status., Methods: A total of 202 patients with different cancer types and undergoing various treatments completed the COVID-19 Fears Questionnaire for Chronic Medical Conditions, and their vaccination status was evaluated. Patients' behaviors were monitored using a smartphone application that passively and continuously captures high-resolution data from personal smartphone sensors. In all, 107 patients were monitored for at least 2 weeks. The study was conducted between August 2022 and August 2023. Distributions of clinical and demographical parameters between fully vaccinated, partially vaccinated, and unvaccinated patients were compared using the Chi-squared test. The fear of COVID-19 among the groups was compared using the Mann-Whitney and the Kruskal-Wallis criteria. Trajectories of passively generated data were compared as a function of fear of COVID-19 and COVID-19 vaccination status using local polynomial regression., Results: In total, 202 patients were included in the study. Most patients were fully (71%) or partially (13%) vaccinated and 16% of the patients were unvaccinated for COVID-19. Fully vaccinated or unvaccinated patients reported greater fear of COVID-19 than partially vaccinated patients. Fear of COVID-19 was higher in patients being treated with biological therapy. Patients who reported a higher fear of COVID-19 spent more time at home, visited places at shorter distances from home, and visited fewer places of interest (POI). Fully or partially vaccinated patients visited more POI than unvaccinated patients. Local polynomial regression using passively generated smartphone sensor data showed that, although at the beginning of the study, all patients had a similar number of POI, after 1 week, partially vaccinated patients had an increased number of POI, which later remained, on average, around four POI per day. Meanwhile, fully vaccinated or unvaccinated patients had a similar trend of POI and it did not exceed three visits per day during the entire treatment period., Conclusion: The COVID-19 pandemic continues to have an impact on the behavior of cancer patients even after the termination of the global pandemic. A higher perceived fear of COVID-19 was associated with less movement, more time spent at home, less time spent outside of home, and a lower number of visited places. Unvaccinated patients visited fewer places and were moving less overall during a 14-week follow-up as compared to vaccinated patients., Competing Interests: Author RB was employed by ProIT. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kasputytė, Jenciūtė, Šakinis, Bunevičienė, Korobeinikova, Vaitiekus, Inčiūra, Jaruševičius, Bunevičius, Krikštolaitis, Krilavičius, Juozaitytė and Bunevičius.)

Background: Timely recognition of cancer progression and treatment complications is important for treatment guidance. Digital phenotyping is a promising method for precise and remote monitoring of patients in their natural environments by using passively generated data from sensors of personal wearable devices. Further studies are needed to better understand the potential clinical benefits of digital phenotyping approaches to optimize care of patients with cancer., Objective: We aim to evaluate whether passively generated data from smartphone sensors are feasible for remote monitoring of patients with cancer to predict their disease trajectories and patient-centered health outcomes., Methods: We will recruit 200 patients undergoing treatment for cancer. Patients will be followed up for 6 months. Passively generated data by sensors of personal smartphone devices (eg, accelerometer, gyroscope, GPS) will be continuously collected using the developed LAIMA smartphone app during follow-up. We will evaluate (1) mobility data by using an accelerometer (mean time of active period, mean time of exertional physical activity, distance covered per day, duration of inactive period), GPS (places of interest visited daily, hospital visits), and gyroscope sensors and (2) sociability indices (frequency of duration of phone calls, frequency and length of text messages, and internet browsing time). Every 2 weeks, patients will be asked to complete questionnaires pertaining to quality of life (European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire [EORTC QLQ-C30]), depression symptoms (Patient Health Questionnaire-9 [PHQ-9]), and anxiety symptoms (General Anxiety Disorder-7 [GAD-7]) that will be deployed via the LAIMA app. Clinic visits will take place at 1-3 months and 3-6 months of the study. Patients will be evaluated for disease progression, cancer and treatment complications, and functional status (Eastern Cooperative Oncology Group) by the study oncologist and will complete the questionnaire for evaluating quality of life (EORTC QLQ-C30), depression symptoms (PHQ-9), and anxiety symptoms (GAD-7). We will examine the associations among digital, clinical, and patient-reported health outcomes to develop prediction models with clinically meaningful outcomes., Results: As of July 2023, we have reached the planned recruitment target, and patients are undergoing follow-up. Data collection is expected to be completed by September 2023. The final results should be available within 6 months after study completion., Conclusions: This study will provide in-depth insight into temporally and spatially precise trajectories of patients with cancer that will provide a novel digital health approach and will inform the design of future interventional clinical trials in oncology. Our findings will allow a better understanding of the potential clinical value of passively generated smartphone sensor data (digital phenotyping) for continuous and real-time monitoring of patients with cancer for treatment side effects, cancer complications, functional status, and patient-reported outcomes as well as prediction of disease progression or trajectories., International Registered Report Identifier (irrid): PRR1-10.2196/49096., (©Gabrielė Jenciūtė, Gabrielė Kasputytė, Inesa Bunevičienė, Erika Korobeinikova, Domas Vaitiekus, Arturas Inčiūra, Laimonas Jaruševičius, Romas Bunevičius, Ričardas Krikštolaitis, Tomas Krilavičius, Elona Juozaitytė, Adomas Bunevičius. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 10.10.2023.)

Background and Objectives : To our knowledge, this is the first study that investigated the prognostic value of radiomics features extracted from not only staging 18F-fluorodeoxyglucose positron emission tomography (FDG PET/CT) images, but also post-induction chemotherapy (ICT) PET/CT images. This study aimed to construct a training model based on radiomics features obtained from PET/CT in a cohort of patients with locally advanced head and neck squamous cell carcinoma treated with ICT, to predict locoregional recurrence, development of distant metastases, and the overall survival, and to extract the most significant radiomics features, which were included in the final model. Materials and Methods : This retrospective study analyzed data of 55 patients. All patients underwent PET/CT at the initial staging and after ICT. Along the classical set of 13 parameters, the original 52 parameters were extracted from each PET/CT study and an additional 52 parameters were generated as a difference between radiomics parameters before and after the ICT. Five machine learning algorithms were tested. Results : The Random Forest algorithm demonstrated the best performance (R 2 0.963-0.998) in the majority of datasets. The strongest correlation in the classical dataset was between the time to disease progression and time to death ( r = 0.89). Another strong correlation ( r ≥ 0.8) was between higher-order texture indices GLRLM&#95;GLNU, GLRLM&#95;SZLGE, and GLRLM&#95;ZLNU and standard PET parameters MTV, TLG, and SUVmax. Patients with a higher numerical expression of GLCM&#95;ContrastVariance, extracted from the delta dataset, had a longer survival and longer time until progression ( p = 0.001). Good correlations were observed between Discretized&#95;SUVstd or Discretized&#95;SUVSkewness and time until progression ( p = 0.007). Conclusions : Radiomics features extracted from the delta dataset produced the most robust data. Most of the parameters had a positive impact on the prediction of the overall survival and the time until progression. The strongest single parameter was GLCM&#95;ContrastVariance. Discretized&#95;SUVstd or Discretized&#95;SUVSkewness demonstrated a strong correlation with the time until progression.

(1) Background. Breast cancer is the leading cancer type among women. Despite convenient diagnostics at early stages, there is a need for continuous monitoring to predict more aggressive or recurring breast cancer forms. The evidence suggests that the detection of genetic biomarkers could help in improving disease management and reduce mortality. Matrix metalloproteinases (MMPs) are a large family of enzymes that perform physiologically relevant functions and have the potential properties to be biomarkers for cancer assessment. We aimed to evaluate the contribution and association of single-nucleotide polymorphisms (SNPs) in MMP genes ( MMP1 , MMP2 , MMP3 , MMP7 , MMP8 , MMP9 ) with clinicopathological breast-cancer features. (2) Methods. In this study, 100 breast cancer patients were genotyped by polymerase chain reaction-restriction fragment length polymorphism methodology (PCR-RFLP). (3) Results. The presence of the MMP7 rs11568818 A allele was associated with lower chances for poorly differentiated breast cancer. The lower possibility for HER2-positive breast cancer was associated with the presence of the MMP9 rs3918242 C allele. (4) Conclusions. These results indicate that MMP7 rs11568818 and MMP9 rs3918242 are potential biomarkers for the anticipation of breast cancer aggressiveness.

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis-related genes TP53 , BBC3 , CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

Purpose: Breast cancer is the most frequent female cancer, leading to relapse with distant metastasis of approximately one-third of patients. Cancer is usually considered a genetic disease involving mutations in nuclear DNA. However, genes, coding for mitochondrial proteins or regulatory molecules, are rarely under consideration. This study aimed to analyse 10 single nucleotide variants in POLG and TFAM genes and assess their association with tumour phenotype and disease outcome., Materials and Methods: A total of 234 breast cancer patients were included in this study. Variations were determined with Real-Time PCR using TaqMan ® probes., Results: We found that patients with POLG rs2307441 TT and CT genotypes had a lower probability for vascular invasion than those with CC genotype ( p =  0.001). Patients with POLG rs2072267 AG genotype were predisposed for progression compared with GG genotype ( p =  0.015). TFAM rs3900887 TT genotype was associated with a higher probability for positive oestrogen receptors ( p =  0.003) and lymphatic invasion ( p =  0.001) in comparison to AA genotype, patients with TT ( p =  0.000) were more likely to have positive lymph nodes., Conclusions: Our data suggest that variations in POLG and TFAM genes are important determinacies of tumour phenotype and disease outcome in breast cancer patients.

Background: Genetic variations in oxidative stress-related genes may alter the coded protein level and impact the pathogenesis of breast cancer., Methods: The current study investigated the associations of functional single nucleotide polymorphisms in the NFE2L2 , HMOX1, P21 , TXNRD2 , and ATF3 genes with the early-stage breast cancer clinicopathological characteristics and disease-free survival, metastasis-free survival, and overall survival. A total of 202 Eastern European (Lithuanian) women with primary I-II stage breast cancer were involved. Genotyping of the single nucleotide polymorphisms was performed using TaqMan single nucleotide polymorphisms genotyping assays., Results: The CA+AA genotypes of P21 rs1801270 were significantly less frequent in patients with lymph node metastasis and larger tumor size ( P =0.041 and P =0.022, respectively). The TT genotype in ATF3 rs3125289 had significantly lower risk of estrogen receptor (ER), progesterone receptor (PR) negative, and human epidermal growth factor receptor 2 (HER2) positive status ( P =0.023, P =0.046, and P =0.040, respectively). In both, univariate and multivariate Cox analysis, TXNRD2 rs1139793 GG genotype vs. GA+AA was a negative prognostic factor for disease-free survival (multivariate hazard ratio (HR) 2.248; P =0.025) and overall survival (multivariate HR 2.248; P =0.029). The ATF3 rs11119982 CC genotype in the genotype model was a negative prognostic factor for disease-free survival (multivariate HR 5.878; P =0.006), metastasis-free survival (multivariate HR 4.759; P =0.018), and overall survival (multivariate HR 3.280; P =0.048)., Conclusion: Our findings suggest that P21 rs1801270 is associated with lymph node metastasis and larger tumor size, and ATF3 rs3125289 is associated with ER, PR, and HER2 status. Two potential, novel, early-stage breast cancer survival biomarkers, TXNRD2 rs1139793 and ATF3 rs11119982, were detected. Further investigations are needed to confirm the results of the current study.

Breast cancer is one of the most common cancers worldwide. Single nucleotide polymorphisms (SNPs) in MDM2 and MDM4 have been associated with various cancers. However, the influence on clinical characteristics of breast cancer has not been sufficiently investigated yet. Thus, this study aimed to investigate the relationship between SNPs in MDM2 (rs2279744, rs937283, rs937282) and MDM4 (rs1380576, rs4245739) and I-II stage breast cancer. For analysis, the genomic DNA was extracted from 100 unrelated women peripheral blood. Polymorphisms were analyzed with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The study showed that MDM2 rs937283 and rs937282 were significantly associated with estrogen receptor status and human epidermal growth factor receptor 2 (HER2) status. SNPs rs1380576 and rs4245739, located in MDM4 , were significantly associated with status of estrogen and progesterone receptors. Our findings suggest that rs937283 AG, rs937282 CG, rs1380576 CC, and rs4245739 AA genotypes were linked to hormonal receptor positive breast cancer and may be useful genetic markers for disease assessment.

Genetic variations in inflammation- and angiogenesis-related genes may alter the coded protein level and impact the pathogenesis of breast cancer (BC). The present study investigated the association of functional single nucleotide polymorphisms (SNPs) in the VEGFA, IL-1β, IL-1α and IL-6 genes with the early-stage BC phenotype and survival. Genomic DNA and clinical data were collected for 202 adult Eastern European (Lithuanian) women with primary I-II stage BC. Genotyping of the SNPs was performed using TaqMan SNP genotyping assays. Nine VEGFA, IL-1β, IL-1α and IL-6 polymorphisms were analysed. The VEGFA and IL-6 haplotypes were inferred using Phase software. Patients were prospectively followed-up for recurrence, occurrence of metastasis and mortality until April 30, 2019. All studied genotypes were in Hardy-Weinberg equilibrium and had the same distribution as the 1,000 Genomes project Phase 3 dataset for European population. Significant associations of the studied SNPs with clinicopathologic variables were observed between IL-1α rs1800587 C allele and larger primary tumour size; IL-6 rs1800797 A allele, rs1800797 GA genotype, rs1800795 C allele, IL-6 (rs1800797-re1800795) AC diplotype and hormonal receptor-positive disease; IL-6 rs1800797 A allele and HER2 negative status. In univariate Cox survival analysis, IL-1α rs1800587 CC and IL-6 rs1800797 GG genotype carriers exhibited worse disease-free survival (DFS), metastasis-free survival (MFS) and overall survival (OS). The IL-6 rs1800795 GG genotype was associated with worse OS. IL-6 (rs1800797, rs1800795) GG/GG diplotype carriers had shorter MFS and OS. Multivariate Cox survival analysis revealed that the IL-1α rs1800587 CC genotype was an independent negative prognostic factor for DFS, MFS and OS, and the IL6 GG/GG diplotype was an independent negative prognostic factor for MFS and OS. According to the present study, functional SNPs in the IL-1α and IL-6 genes may contribute to the identification of patients at higher risk of BC recurrence, development of metastases and worse OS among early-stage patients with BC., (Copyright: © Korobeinikova et al.)

Background and objectives: Induction chemotherapy (ICT) before definitive chemoradiation (CRT) gives high response rates in locally advanced squamous cell carcinoma of the head and neck (LA-SCCHN). However, pre-ICT gross tumor volume (GTV) for radiotherapy (RT) planning is still recommended. As 18 F-FDG PET/CT has an advantage of biological tumor information comparing to standard imaging methods, we aimed to evaluate the feasibility of 18 F-FDG PET/CT-based post-ICT GTV delineation for RT planning in LA-SCCHN and to assess the prognostic value of PET parameters: maximum standardized uptake value (SUV max ), metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Methods: 47 LA-SCCHN patients were treated with 3 cycles of ICT (docetaxel, cisplatin, and 5-fluorouracil) followed by CRT (70 Gy in 35 fractions with weekly cisplatin). Pre- and post-ICT PET/CT examinations were acquired. Planning CT was co-registered with post-ICT PET/CT and RT target volumes were contoured according to post-ICT PET. Post-ICT percentage decrease of SUV max , MTV and TLG in primary tumor and metastatic regional lymphnodes (LN) was counted. Loco-regional failure patterns, 3-year progression free (PFS) and overall survival (OS) were evaluated. Results: 3-year PFS and OS rates for study population were 67% and 61% respectively. 31.9% of patients progressed loco-regionally. All progress was localized in high-to-intermediate dose (60⁻70 Gy) RT volumes and none in low dose (50 Gy) volumes. Decrease of SUV max ≥ 74% ( p = 0.04), MTV ≥ 68% ( p = 0.03), TLG ≥ 76% ( p = 0.03) in primary tumor, and LN TLG decrease ≥ 74% ( p = 0.03) were associated with PFS. Decrease of primary tumor SUV max ≥ 74% ( p = 0.04), MTV ≥ 69% ( p = 0.03), TLG ≥ 74% ( p = 0.02) and LN TLG ≥ 73% ( p = 0.02) were prognostic factors for OS. Conclusions: According to our results, 18 F-FDG PET/CT-based post-ICT GTV delineation is feasible strategy without negative impacts on loco-regional control and survival. Percentage decrease of metabolic PET parameters SUV max , MTV and TLG has a prognostic value in LA-SCCHN.

Background: Interleukin-10 and tumor necrosis factor α play an important role in breast carcinogenesis. Genes, encoding those two cytokines, contain single nucleotide polymorphisms, which are associated with differential levels of gene transcription. This study analyzes single nucleotide polymorphisms in interleukin 10 and tumor necrosis factor α genes and their contribution to breast cancer phenotype, lymph node status and survival in a group of young Lithuanian women with early-stage breast cancer patients., Results: We genotyped 100 premenopausal Eastern European (Lithuanian) patients with stage I-II breast cancer, ≤ 50 years old at the time of diagnosis, for interleukin 10 -592A > C, -819C > T and -1082A > G and tumor necrosis factor α -308G > A single nucleotide polymorphisms in the gene promoter region. We used the polymerase chain reaction, namely a restriction fragment length polymorphism method, for a SNP analysis. All genotypes were in Hardy-Weinberg equilibrium and had the same distribution as the HapMap CEU population. Holders of IL10 -592A > C heterozygous IL10 -592 AC genotype had a higher probability of estrogen receptor positive breast cancer phenotype than homozygous variants (P = 0.017). Phased ACC haplotype of IL10 polymorphisms was associated with younger age of diagnosis (P = 0.017). Of all the tested single nucleotide polymorphisms, only TNFα -308G > A has revealed a prognostic capability for breast cancer survival. GA genotype carriers, compared to GG, showed a significant disadvantage in progression-free survival (P = 0.005, adjusted hazard ratio (HR) = 4.631, 95 % confidence interval (CI) = 1.587 - 13.512), metastasis-free survival (P = 0.010, HR = 4.708, 95 % CI = 1.445 - 15.345) and overall survival (P = 0.037, HR = 4.829, 95 % CI = 1.098 - 21.243)., Conclusions: According to our data, IL10 -1082A > G, -819 T > C, -592A > C polymorphisms and phased haplotypes have not revealed a prognostic value for breast cancer. On the contrary, the TNFα -308 polymorphism might modulate the risk and contribute to the identification of patients at a higher risk of breast cancer recurrence, metastasis and worse overall survival among young Lithuanian early-stage breast cancer patients.