A pinboard by
Ella Tyuryumina

Research Assistant, International Laboratory for Intelligent Systems and Structural Analysis at National Research University Higher School of Economics


Prediction of distant metastases appearance can save lives of breast cancer patients

In order to understand growth processes of BC on each stage the CoMBreC was proposed as a new research tool. The CoMBreC is threefold: CoMPaS (stages I-II), CoM-III (stage III) and CoM-IV (stage IV). A new model rests on exponential growth model and complementing formulas. For the first time, it allows us to calculate different growth periods of PT and MTS in patients with/without lymph nodes MTS: 1) "non-visible period" for PT; 2) "non-visible period" for MTS; 3) "visible period" for MTS. Calculations via CoMBreC correspond to survival data considering stage of BC. It may help to improve predicting accuracy of BC process using an original mathematical model referred to CoMBreC and corresponding software. Consequently, thesis concentrated on: 1) modelling the whole natural history of PT and MTS in patients with/without lymph nodes MTS; 2) developing adequate and precise CoMBreC that reflects relations between PT and MTS; 3) analysing the CoMBreC scope of application. The CoMBreC was implemented to iOS application as a new predictive tool: 1) is a solid foundation to develop future studies of BC models; 2) does not require any expensive diagnostic tests; 3) is the first predictor of survival in breast cancer that makes forecast using only current patient data.


Endocrine sensitivity is decisive for patient outcome in small node-negative breast cancers (BC) (pT1a,b) - results from the Munich Cancer Registry.

Abstract: In clinical routine, adjuvant systemic therapy in small node-negative (N0) BC is controversial, in particular in HER2-positive disease. We aimed to evaluate outcome of consecutive patients with small N0 BC in a population-based cancer registry and thus consequently substantiate indications for chemotherapy in those patient subgroups at increased relapse risk or poor survival.From 2002 to 2009 (median follow-up 6 years), 9707 primary breast cancer patients with N0 tumors <2 cm (pTis, pT1N0M0) were reported to the Munich Cancer Registry. Patients with pTis tumors (n = 1870) served as internal comparator. Time to progression, observed (OS) and relative survival rates (Kaplan-Meier estimates) are presented. Cox regression analysis was used to assess the influence of tumor size, age, HR-, and HER2-status.10-year-OS for pTis was 94.0%. In HR-positive tumors it was 91.9% in pT1a, 90.6% in pT1b, and 86.8% in pT1c. In HR-negative tumors, rates were 91.7%, 86.8%, and 86.8%, respectively. In HER2-positive tumors it was 81.2%, 88.1%, and 86.7%, in HER2-negative 93.1%, 90.6%, and 86.0%, respectively. In the multivariate model, age, tumor size, and HR-status showed a significant impact on OS (HRneg. vs. HRpos.: hazard ratio 1.50 (95% CI; 1.12-1.99), while HER2-status was not an independent prognostic factor.Prognosis of N0 tumors <1 cm is excellent, especially if they are HR-positive, even in HER2-positive cases. Weighing potential benefits vs. side-effects, there seems to be no need for chemotherapy in tumors <0.5 cm. In pT1b chemotherapy may be considered, if tumors are triple negative or HER2-positive and HR-negative. In pT1c guideline-based adjuvant therapy using all therapeutic options seems to be warranted.

Pub.: 30 Dec '14, Pinned: 15 Jun '17

Carbon dating cancer: defining the chronology of metastatic progression in colorectal cancer.

Abstract: Patients often ask oncologists how long a cancer has been present before causing symptoms or spreading to other organs. The evolutionary trajectory of cancers can be defined using phylogenetic approaches but lack of chronological references makes dating the exact onset of tumours very challenging.Here we describe the case of a colorectal cancer patient presenting with synchronous lung metastasis and metachronous thyroid, chest wall and urinary tract metastases over the course of five years. The chest wall metastasis was caused by needle tract seeding, implying a known time of onset.Using whole genome sequencing data from primary and metastatic sites we inferred the complete chronology of the cancer by exploiting the time of needle tract seeding as an in vivo 'stopwatch'. This approach allowed us to follow the progression of the disease back in time, dating each ancestral node of the phylogenetic tree in the past history of the tumour. We used a Bayesian phylogenomic approach, which accounts for possible dynamic changes in mutational rate, to reconstruct the phylogenetic tree and effectively "carbon date" the malignant progression.The primary colon cancer emerged between five and eight years prior to the clinical diagnosis. The primary tumour metastasised to the lung and the thyroid within a year from its onset. The thyroid lesion presented as a tumour-to-tumour deposit within a benign Hurthle adenoma. Despite rapid metastatic progression from the primary tumour, the patient showed an indolent disease course. Primary cancer and metastases were microsatellite stable and displayed low chromosomal instability. Neo-antigen analysis suggested minimal immunogenicity.Our data provide the first in vivo experimental evidence documenting the timing of metastatic progression in colorectal cancer and suggest that genomic instability might be more important than the metastatic potential of the primary cancer in dictating colorectal cancer fate.

Pub.: 23 Mar '17, Pinned: 15 Jun '17

Metastatic breast cancer: we do need primary cost data.

Abstract: The lifetime cost of metastatic breast cancer is a key component for the economic evaluations of targeted therapies and biomarkers. In the literature, only few cost studies are available and provide discordant cost estimates for the management of metastatic recurrences. Our objective was to assess the lifetime costs of metastatic breast cancer and to investigate cost variability using primary cost data. We used individual data from a cohort of 290 French women treated at the Gustave Roussy Institute and who had died between 2005 and 2008. We separately analysed the determinants for survival after metastatic recurrence and for the monthly cost using two different models. The mean survival time after recurrence was 24.8 months. The mean hospital cost per patient amounted to € 36,516 and the mean cost per month € 3764. We identified three prognostic factors: age at breast cancer diagnosis, the histological grade and the site of the first recurrence. The factors significantly associated with the cost per month were hospitalisation in a palliative care unit, trastuzumab treatment, the number of sites of recurrence and whether or not the patient had died during the last hospital stay. We identified cost drivers of the lifetime costs of metastatic breast cancer. This provides useful information for the design of future economic studies. We also provide cost estimates in homogeneous subgroups of patients defined by patient characteristics and by the type of care received.

Pub.: 24 Apr '12, Pinned: 15 Jun '17