Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer

Abstract A growing number of early-stage lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomography. But pure solid T1 lung cancer with ≤3 cm in the greatest dimension is not always at an early stage, despite its small size. This type of cancer can be highly aggressive and is associated with pathological involvement, metastasis, postoperative relapse, and even death. However, it is easily misdiagnosed or delay diagnosed in clinics and thus poses a serious threat to human health. The percentage of nodal or extrathoracic metastases has been reported to be >20% in T1 lung cancer. As such, understanding and identifying the aggressive characteristics of pure solid T1 lung cancer is crucial for prevention, diagnosis, and therapeutic strategies, and beneficial to improving the prognosis. With the widespread of lung cancer screening, these highly invasive pure solid T1 lung cancer will become the main advanced lung cancer in future. However, there is limited information regarding precision medicine on how to identify these “early-stage” aggressive lung cancers. To provide clinicians with new insights into early recognition and intervention of the highly invasive pure solid T1 lung cancer, this review summarizes its clinical characteristics, imaging, pathology, gene alterations, immune microenvironment, multi-omics, and current techniques for diagnosis and prediction.


Introduction
2][3] A growing number of earl y-sta ge lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomogr a phy. 4 But pure solid T1 ( T1, ≤3 cm in the greatest dimension ) lung cancer is not always early-stage lung cancer.A pure-solid nodule was defined as a consolidation tumour ratio equal to 1.0 and without a ground-glass opacity component on chest Computed Tomogr a phy ( CT ) .It can exhibit highl y a ggr essiv e behavior which is associated with pathological in volvement, metastasis , postoper ativ e r ela pse, and e v en death. 5 , 6It has been reported that the percentage of nodal or extr athor acic metastases is > 20% in T1 lung cancer, [7][8][9][10] , i.e. some pure solid T1 lung cancer patients are diagnosed after the development of symptoms with metastatic sites .T he a ggr essiv e behaviour may be linked to differences in cellular pr olifer ation and inv asion ca pabilities, [11][12][13][14][15][16] is easy to misdiagnose or delay diagnosis in clinics and poses a serious threat to human health.
Understanding the demogr a phic and biological c har acteristics of pure solid T1 lung cancer is critical for matching appropriate patients with individualized ther a py str ategies and for ecasting pr ognoses.A pr oportion of pur e-solid nodules r e v eal a pur e solid a ppear ance at the outset, while the r emainder e volv e fr om ground-glass nodules. 17 , 180][21] Small solitary lung cancers whic h occur in males, younger patients, or locate in the main br onc hus or left lung, or with histologic type as small cell lung cancer, or with undifferentiated type, tend to hav e extr a-thor acic metastasis. 22Ho w e v er, ther e is limited information on how to identify patients with these "earl y-sta ge" lung cancers who present with aggr essiv e c har acteristics .T her efor e, this r e vie w focuses on summarizing the c har acteristics of the clinic, ima ging, pathology, driver gene and single-cell m ulti-omics, mac hine learning, artificial intelligence ( AI ) , and current methods for the diagnosis and prediction of highly invasive pure solid T1 lung cancer to improve early recognition and intervention for clinicians.

Ev alua ting the aggressive c har acteristics of pure solid T1 lung cancer by chest CT images
Tumour size of lung cancer is associated with nodal upstaging, e v en in T1 diseases. 23Pure solid tumours may have a worse prognosis than part-solid tumours in stage IA patients according to the eighth edition tumor node metastasis ( TNM ) classification, and similar results were found for the T1a-1b and T1b-1c subgroups. 24atients with a tumour size of T1b-1c ( between 2 and 3 cm in size ) exhibited more frequent nodal upstaging than those with a T1a-1b tumour size of ≤2 cm. 25 , 26 Shin found that the prognosis of pure solid tumors remained worse, while the maximum tumour size of part solid tumours is larger than that of pure solid tumours. 27Hu et al .found that the incidence of extr a-thor acic metastasis ( M1b ) in all small solitary lung cancer ( ≤2 cm ) is 6.31% ( 692/10 968 ) , and the incidence is ele v ated r a pidl y with an increase of the tumour size, from 0.98% in lesions ≤10 mm to 5.33% in lesions 11 to 20 mm in diameter.But the difference between solid T1 lung cancer and ground glass opacity ( GGO ) T1 lung cancer was not illustrated in their study. 22Tumour location at CT in the inner one-third of the lung, defined by concentric lines arising from the hilum, was adv ersel y associated with survival and sho w ed moderate interr eader a gr eement. 28The centr al location may be associated with lymph node metastasis, but the tumour location seemed to have less impact on a GGO-predominant lesion. 29Density is regarded as a more important factor than location in e v aluating the a ggr ession of lung cancer.Ne v ertheless, it is difficult to identify the tumour density on High Resolution CT ( HRCT ) ima ges, whic h complicates classification of a tumour area as solid or as a GGO component. 30 thological fea tures are still an essential factor for distinguishing in vasi ve pure solid T1 lung cancer Solid lung cancer nodules are common presentations of various histological types, including adenocarcinoma, squamous cell carcinoma ( SCC ) , and neuroendocrine tumours ( NETs ) .2][33] Adenocarcinoma is the most common histopathological type in non-small cell lung cancer ( NSCLC ) and is mostly prone to nodal upstaging in T1N0 disease. 24 , 27 , 346][37] Ho w ever, lung adenocar cinoma demonstrating lepidic growth ( growth along alveolar walls ) is a significantly favour able pr ognostic factor for pT1 NSCLC in m ultiple studies, despite showing a pure-solid appearance. 38 , 391][42] SCC used to be a r epr esentativ e histological type of centr all y located lung cancer, but an increasing number of peripheral SCCs have been reported.A r etr ospectiv e inv estigation found that peripher al-type SCC had a lo w er pathological stage, less lymphatic and vessel involv ement, and fe wer l ymph node metastases, but ther e was no significant difference in overall survival compared to centraltype SCC.In contrast, the present study sho w ed that even smallsized SCCs in the peripheral lung may have malignant potential, such as a higher incidence of pleural, vascular, and lymphatic invasion. 314][45][46] But some studies found no difference in prognosis between SCC and solid adenocarcinoma. 31 , 47NETs of the lung with distinct clinical behavior constitute ∼20% of all primary lung tumours, including lowgr ade typical carcinoids, intermediate-gr ade atypical carcinoids, high-gr ade lar ge cell neur oendocrine tumours, and small cell lung cancer.Histologic grade was the dominant driver of prognosis in patients with NETs.NETs appear as solitary tumours on CT, and their oncological behaviours ar e r emarkabl y differ ent. 48Another stud y re ported that small cell lung cancer or with undifferentiated type tend to have extra-thoracic metastasis .T hus , pathological type is an essential factor for distinguishing the inv asiv e T1 lung cancer. 22iscer al pleur al inv asion ( VPI ) ma y ha v e a mor e significant association with poor prognosis in pure-solid tumours than in partsolid tumours.Some studies have suggested that cancer cells can spr ead thr ough the pleur al cavity and l ymphatics to the mediastinal lymph nodes, and upstaging of the T-category by VPI in T1sized NSCLCs may be more applicable for pure-solid tumours. 49PI indicates poor prognosis and is defined as a T2 descriptor for T1-sized tumours. 50 , 51On the other hand, v ascular inv asion was identified as a poor-prognosis factor, e v en in sta ge IA NSCLC, because of a higher rate of distant metastasis . 31T her efor e, e v aluating the pathological VPI and v ascular inv asion is useful for predicting the inv asiv eness of T1 solid lung cancer.

Different c har acteristics of molecular pathogenesis may drive invasiveness in the different stages of T1 lung cancer
According to the pr ogr ession sc hema, gene alter ations should be e v enl y accum ulated along the entir e pr ogr ession of lung cancer.Epidermal Growth Factor Receptor ( EGFR ) -mutated tumours were e v enl y distributed along each progression step . 17 , 52In the T1c radiologicall y pur e-solid lung adenocarcinoma subset, the EGFRm utant gr oup exhibited mar ginall y lo w er 5-y ear Recurrence F ree Survival ( RFS ) than the EGFR wild-type group . 17Furthermore, Kirsten Rat Sarcoma viral oncogene ( KRAS ) mutations are detected in 33% of Atypical Adenomatous Hyperplasia ( AAH ) , 12% of carcinomas in situ , 8% of minimall y inv asiv e adenocarcinoma, and 0% of well-differentiated adenocarcinoma, which appear to decrease along the progression. 53Strikingly, Caucasians and smokers seemed to de v elop mor e r a pidl y pr ogr essiv e NSCLC, and the presence of a KRAS mutation may be responsible for the r a pid pr ogr ession of NSCLCs in Caucasian patients in some studies. 19ompared with subsolid nodule lung adenocarcinomas, solid nodule lung adenocarcinoma harboured higher somatic mutation counts, genomic alteration counts, and intratumour heterogeneity, and sho w ed a lo w er incidence of EGFR mutation but a higher frequency of genes such as Tumor Protein P53 ( TP53 ) , AT-rich inter activ e domain-containing protein 1A ( ARID1A ) , Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform ( PIK3CA ) , Recombinant Cyclin Dependent Kinase Inhibitor 2A ( CDKN2A ) , and Blac k Roc k Arts Foundation ( BRAF ) in terms of dri ver genes.In ad dition, the y had a significantly higher number of pathwa y alterations , including p53, cell cycle, and phosphoinositide 3 kinase ( PI3K ) , indicating that solid nodule lung adenocarcinomas had a less complex genomics arc hitectur e ov er all. 54Howe v er, the molecular mec hanisms underl ying this phenomenon ar e not yet clear.
P athological nodal involv ement was also thought to be a valuable prognostic factor in patients with pure-solid stage I NSCLC. 55usion mutation was a significant risk factor for lymph node metastasis among stage T1 NSCLC.In Shin's study, Anaplastic Lymphoma Kinase ( ALK ) r earr angement was corr elated with mor e r egional l ymph node metastasis and unfavour able disease-fr ee surviv al compar ed to ALK-negativ e patients in patients with completel y r esected sta ge IA lung adenocarcinoma. 56Similarl y, ROS proto-oncogene 1 ( ROS1 ) status was significantly associated with lymph node metastasis, and R OS1 positivity w as found to be higher in patients at advanced node stages. 57Additionally, patients who possess the proto-oncogene tyrosine-protein kinase receptor Ret ( RET ) fusion gene tended to present with more N2 stage ( 54.5% ) in small tumours ( ≤3 cm ) , significantly higher than the other lung adenocarcinomas without RET fusion ( 22.6% ) . 58Therefore, the fusion mutant protein may be a predictor for lymph node metastasis of solid T1 lung cancer.

Multiomics sequencing analysis is an important technique to evaluate the in vasi veness of T1 solid lung cancer and needs to be further de v eloped
The presented studies that used multi-omics techniques to analyse the inv asiv eness of T1 lung cancer mainly focus on comparing the differences between solid T1 lung adenocarcinoma and T1 GGO lung adenocar cinoma.Adenocar cinomas exhibiting as solid nodules are often more aggressive and are characterized by a higher r ecurr ence r ate after r esection. 59While m ultiple tr eatment modalities hav e substantiall y impr ov ed clinical outcomes for patients with adenocarcinoma, the treatment r esponse can v ary widel y, r anging fr om long-term r emission to r a pid pr ogr ession. 60 , 61Conventional bulk sequencing has uncovered abundant molecular aberrations that drive carcinogenesis and the pr ogr ession of adenocarcinoma.More advanced techniques, such as single-cell RN A sequencing ( scRN A-seq ) , are r equir ed to compr ehensiv el y decipher the underl ying molecular mechanism and indicate the heterogeneity of adenocarcinoma. 62Tao conducted single-cell RNA sequencing on fresh surgical specimens obtained from eight resectable adenocarcinoma cases, of which four were identified as pure GGO and the remaining four as solid nodules on CT imaging.The results of the study indicated that the antitumour immunity mediated by natural killer ( NK ) and CD8 + T cells gradually weakened as adenocarcinoma pr ogr essed, while humor al imm unity mediated by plasma B cells was more active in solid nodules .Moreo ver, stromal cells and M2 macr opha ges wer e found to pr omote the pr ogr ession of adenocarcinoma.Thr ough compr ehensiv e anal yses , they disco ver ed dynamic c hanges in cellular components and intercellular interactions during the progression of adenocarcinoma.Lu et al .found that cancer cells derived from solid adenocarcinoma had a high-grade malignancy compared with those from GGO adenocarcinoma based on scRNA-seq results. 63he imm une micr oenvir onment was mor e activ e in solid nodule-associated adenocarcinomas than in GGO-associated adenocarcinomas, including more expression of immune-related genes, upregulation of immune pathwa ys , more infiltration of immune cells, and an expanded TCR repertoire. 64The tumour imm une micr oenvir onment, especiall y tumour-infiltr ating T cells, plays a pivotal role in the occurrence and development of tumours.Limited evidence has shown that the infiltration of tumor associated macr opha ges ( TAMs ) and Regulatory ( Treg ) cells and the expression of TGF-β are significantly higher in solid lung adenocarcinoma than in GGO-lung adenocarcinoma.The infiltration of the remaining immune cells, including CD8 + T cells, CD4 + T cells , CD103 + T cells , CD20 + B cells , and CD138 + plasma cells, did not seem to be significantly different in GGO-lung adenocarcinoma, although there was no significant difference in PD-L1 expression in the two cohorts. 52It is necessary to explore the differences in the immune microenvironment in highly aggressive pure solid T1 lung cancer in future.Multi-omics analysis has also revealed that solid-associated lung cancers are characterized by a mor e activ e metabolism and imm une micr oenvir onment, whic h may also be r ele v ant to their a ggr essiv e clinical course. 65These findings highlight the importance of considering both molecular and immune factors in understanding the biology of solid T1 lung cancer and de v eloping ne w tr eatment str ategies, but the underl ying mec hanisms driving tumour pr ogr ession and the intertumour al and intr atumour al cellular and molecular heter ogeneity in T1 solid lung cancer are limited. 66 , 67nalysing the spatial transcriptomic information of highly inv asiv e lung cancer nodules is of the utmost importance for further understanding the mechanisms underlying metastasis.Ho w e v er, curr entl y, ther e ar e no r ele v ant r eports av ailable, primarily due to the limited availability of samples .T he population with metastatic lung cancer is usually classified as locally advanced or advanced stages, where surgical resection is not r ecommended.Obtaining samples fr om these patients thr ough non-sur gical methods, suc h as non-sur gical biopsies in medical departments, pr esents c hallenges as it yields a small sample size and makes it difficult to pr eserv e the spatial structure, thus limiting the ability to accur atel y r eflect the spatial arc hitectur e of the tumour.Despite these challenges, the direction of this research is highl y pr omising and deserv es attention.With adv ancements in detection and sampling techniques, we anticipate that valuable insights into the tr anscriptomic landsca pe of highl y inv asiv e lung cancer nodules and their metastatic mechanisms will be obtained.
T he abo v e information about pr ediction of a ggr essiv e c har acteristics has been summarized in Table 1 .

Advances in prediction for aggression of pure solid T1 lung cancer
Confirming the presence of pure solid lung cancer before an inv asiv e pr ocedur e is c hallenging in clinical pr actice, especiall y in earl y sta ges.Se v er al r esearc h findings indicated that iodine uptake in the arterial phase on contrast CT of primary lung cancer may be associated with some aspects of tumour histopathology, such as angiogenesis, differentiation grade , hypoxic cells , and tumour inv asiv eness. 68 , 69A low 3D-Iodine-related attenuation at the early phase of solid lung cancers has been significantly associated with pathological inv asiv eness and postoper ativ e r ecurr ence, as well as a higher TNM sta ge, pleur al inv asion, c hest wall invasion, intr a pulmonary metastasis, l ymph node metastases, and poor er pr ognosis .T hese findings ma y help identify patients with earl y-sta ge lung cancer who have a higher risk of a ggr essiv e disease and may r equir e mor e a ggr essiv e tr eatment str ategies. 70n the other hand, the differences in malignant behaviour can be identified using maximum standardized uptake values ( SUV ) determined by F-18-fluorodeoxyglucose positron emission tomogr a phy/computed tomogr a phy ( PET-CT ) . 71The SUVmax le v el corr elated well with the histologic subtypes based on the International Association for the Study of Lung Cancer /American Thoracic Society / European Respiratory Society ( IASLC/ATS/ETS ) classification, e v en for cases of stage IA solid lung cancer. 72Howe v er, it should be noted that the accuracy of PET-CT for detecting lymph node metastasis is not always sufficient, particularly in r egions wher e tuberculosis is endemic, due to the potential for false-positives caused by granulomatous inflammation. 73eanwhile, se v er al studies hav e demonstr ated the potential of deep learning algorithms in predicting the a ggr essiv eness and prognosis for lung cancer.Deep Cubical Nodule Transfer Learning Algorithm ( CUBIT ) , a deep learning algorithm using transfer learning and 3D Convolutional Neural Networks ( CNN ) , can accur atel y pr edict l ymphov ascular inv asion ( LVI ) or nodal involvement in T1 size NSCLC on CT ima ges, whic h may be helpful in individualizing treatment.Tau developed a CNN for PET images to accur atel y designate the N category of pr e viousl y untr eated NSCLC patients. 74Ho w e v er, an integr ated deep learning a ppr oac h that combines m ultimodal ima ging data with clinical data may be e v en mor e useful in pr edicting LVI or nodal involv ement befor e sur gery. 75Recentl y, we found that the deep learning method can accur atel y pr edict local or distant metastasis in patients with solid T1-stage lung cancer. 76Ho w ever, high-quality mass data are needed to further de v elop and validate the prediction models to identfy the a ggr ession of T1 solid lung cancer.
Liquid biopsy is a promising noninvasive alternative for cancer screening.car cinoembry onic antigen ( CEA ) has been identified as a predictor for mediastinal nodal metastasis in clinical stage IA NSCLC patients, and pr eoper ativ e serum CEA le v els can be used to predict tumour aggressiveness and recurrence in c-T1a lung cancer. 6Tsai also found that CEA alteration was associated with a significantly worse 5-year mortality rate in T1a-bN0M0 NSCLC patients. 77In recent y ears, cir culating tumour DN A ( ctDN A ) has emerged as a promising liquid biopsy biomarker for noninvasive cancer screening and post-treatment surveillance. 78Due to the cell-free DN A ( cfDN A ) abundance of noncancerous origin coupled with its r a pid metabolic r ate, the concentr ation of ctDNA is extr emel y low, especiall y in oper able earl y-sta ge cancers. 79Circulating tumor cells ( CTCs ) are one of the mainstays of liquid biopsy, which also includes circulating tumour DNA ( ctDNA ) , cell-free RNA, extr acellular v esicles , and tumour-educated platelets .CTCs ar e belie v ed to be a pr ecursor of metastasis, contributing to the high mortality rate associated with cancer. 80Furthermore, Ye et al .reported that circulating genetically abnormal cells ( CACs ) presented a significant diagnostic value in detecting lung cancer for patients with pulmonary nodules ≤10 mm. 81In their study, when the cutoff value of CACs was > 2 mm, the sensitivity and specificity for lung cancer were 70.5% and 86.4%, r espectiv el y.Male, maxim um solid nodule, maxim um nodule located in upper lobe, and CACs > 2 mm met the P < 0.10 criterion for inclusion in the m ultiv ariable models. 81W ith adv ancements in tec hnology, futur e studies may be conducted to e v aluate the efficacy of CACs in predicting metastasis of T1 solid lung cancer.Liquid biopsy is continuousl y impr oving, making it a pr omising tool for cancer dia gnosis and monitoring.
To sum up, the current methods for prediction for the a ggr ession of pure solid T1 lung cancer are shown in Fig. 1 .

Perspectives
Predicting oncological behaviours is important for surgical planning and a ggr essiv e surv eillance of the tumour.In clinical and pathological T1N0-staged NSCLC, pure-solid tumours are associated with worse disease-free survival ( DFS ) . 82 , 83The 8th edition of the TNM classification recommends that tumours with the same solid component size be further categorized into part-solid and pure-solid tumours and that they be considered separately due to the more malignant behaviour and poorer prognosis of pure-solid tumours.Lar ger pur e-solid tumours may indicate the need for aggr essiv e adjuv ant or neoadjuv ant ther a p y. 82 Ho w e v er, the factors influencing tumour gr owth r emain poorl y defined, and in the absence of a clear relationship between time and tumour growth in NSCLCs, these factors will be k e y to identifying a ggr essiv e tumours that upstage early and need prompt resection.In the futur e, further explor ation is needed for scr eening, dia gnosis, tr eatment, and follow-up strategies for different early-stage lung cancers with varying degrees of invasiveness to achieve personalized optimal ther a peutic effects.

Figure 1 .
Figure 1.Prediction for aggression of pure solid T1 lung cancer.

Table 1 .
Prediction of aggressive characteristics in pure solid T1 lung cancer.